association for education finance and policy - disrupting or … · 2019-03-25 · disrupting or...

Running head: INEQUALITIES GRANTMAKING 1

Disrupting or preserving privilege?:

The design and causal effects of frames in inequalities grantmaking in U.S. higher education

Heather McCambly

Jeannette Colyvas

Northwestern University

WORKING PAPER

DO NOTE CITE WITHOUT AUTHOR PERMISSION

INEQUALITIES GRANTMAKING 2

WORKING PAPER / DO NOTE CITE WITHOUT AUTHOR PERMISSION

Abstract

Many of today’s public and private grantmaking organizations seek to influence social through

public campaigns to reduce persistent social inequities. Yet, we know little about the material effects of

funder’s ideological stances on their social investment strategies. We examine a federal grantmaking

agency—the Fund for the Improvement of Postsecondary Education (FIPSE)—and its efforts to cultivate

field-level innovation to improve outcomes for minoritized students. We combine 20 years of archival

document analysis with a Difference-in-Difference-in-Difference method of causal inference to trace the

processes of ideological and policy change and to estimate their effects on delivery of grant dollars. Our

findings demonstrate how FIPSE’s adoption of a race and class justice policy frame had significant causal

consequences on the types of colleges and universities to which it awarded grant dollars. And yet, key

grantmaking mechanisms changed simultaneously, leaving intact structures of benefits and burdens that

perpetuate stratification. Instead of diminishing sources of institutional persistence that reproduce

inequalities, this frame change shifted the modes that reproduced the status quo.



Many of today’s public and private grantmaking organizations seek to influence social policy

through expensive public campaigns, often directed at reducing persistent social inequities (Reckhow &

Snyder, 2014; Tompkins-Stange, 2016). These actors are custodians of multiple types of influence—

normative influences (setting priorities, defining terms for the field), coercive influences (awarding or

withholding financial resources), and mimetic influences (providing peer models of best practices)

(DiMaggio & Powell, 1983). Grantmakers can leverage these resources to support the persistence of the

status quo or to support change (Colyvas & Jonsson, 2011). Grantmakers, who have long been

concerned with education as a mode for social change, are expanding their investments in higher

education (Kelly & James, 2015). In the context of social policy, grantmakers’ influence can be

particularly salient in the ways it legitimizes or challenges ideas in the field about how greater social

equality should be achieved, measured, and who deserves it (Reckhow & Tompkins-Stange, 2018).

Indeed, changing policy discourses has itself become a strategy for diminishing inequality. And yet, the

question remains: does adopting changed discourses translate to meaningful disruptions to sources of

social inequality?

This issue is especially relevant in U.S. higher education. While higher education is widely

viewed as one of the critical sites for advancing equal opportunity, as in most domains, such egalitarian

aims often produce myth and ceremony rather than meaningful achievement (Berrey, 2011; Bromley &

Powell, 2012; Meyer, 1977; Meyer & Rowan, 1977). Indeed, in this paper we argue that organizations

dedicated to the social good can simultaneously intervene to change and inadvertently support

consistent, patterned inequality. In the midst of this contradiction, many grantmaking organizations

have converged around urgent calls to “move the needle” on “equity.” And yet, these major federal and

philanthropic investments struggle to undo colleges’ predominantly stratifying effects along lines of race

and class (see, e.g., Bastedo & Jaquette, 2011; Cox, 2016). Ideas about what it would mean to “move



the needle” or to institutionalize changes in educational “equity” are highly contested as actors operate

from varied political and cultural stances about how people and resources should mobilize in relation to

target populations and ideal solutions. While there are many who claim that adopting specific

definitions—or as we refer to them, frames—of equity are key to turning the tide on reforms that

typically serve to reproduce inequality (see, e.g., Witham, Malcom-Piqueux, Dowd, & Bensimon, 2015),

empirical work that causally tests if these framings have material effects on intervention designs are

rare if nonexistent, particularly in higher education.1

We address this gap by examining frame variation within a longitudinal study of a federal

grantmaking agency focused exclusively on improving college environments and outcomes—the Fund

for the Improvement of Postsecondary Education (FIPSE). This study takes as its starting point the

natural experiment afforded by an Obama-era change to FIPSE, which offers a rare opportunity to

examine the impact of elites’ actions in the grantmaking context. First, we ask, how does FIPSE’s

approach, as a combination of policy frames and promoted strategies, shift over time in alignment with

core field-level diversity ideologies, such as color blindness, multiculturalism, and racial and class justice

(RQ1)? Second, we ask, does this approach have a causal effect on FIPSE’s allocation of resources (i.e.

funding and legitimacy) in terms of the types of organizations that benefit from FIPSE funding (RQ2)?

We use archival analysis to address FIPSE’s changing frames and policy designs. We then use a

Difference-in-Difference-in-Difference statistical analysis to test the material effects of these frames on

grants distribution.

By examining grantmaking practices intended to cause institutional change, and the policy

frames through which actors mobilize change strategies, we expose the relationship between

legitimized structures and beliefs in higher education and the persistent direction of benefits to

1 In this study, the idea of intervention “designs” is measured by the variation in organizational types that receive

grant funding, which acts as a proxy for the type of environment and the target population for which innovations are developed.



organizations that will preserve rather than disrupt inequality. These findings demonstrate how FIPSE’s

adoption of a race and class justice policy frame had significant causal consequences on the types of

colleges and universities to which it awarded grant dollars. And yet, FIPSE simultaneously changed key

grantmaking mechanisms, leaving intact structures of benefits and burdens likely to perpetuate

stratification. Instead of diminishing sources of institutional persistence that reproduce educational

inequalities along lines of race and class, this frame change shifted the modes that reproduced the

status quo.

We begin by describing the theoretical and empirical anchors for our work that synthesizes

domain-specific literature on the role of grantmakers in an organizational field with literature on modes

of institutional change and persistence. Using this literature, we identify two sets of hypotheses that

predict frame changes and effects. We then discuss our methodology involving a longitudinal, mixed-

methods study of FIPSE leveraging multiple sources of data—archival and administrative datasets—to

specify both descriptive and causal processes and make causal inferences (Brady & Collier, 2004; Collier,

2011). Next, we report our findings, by first delineating how the agency’s frame and promoted

strategies changed over time, hinging around the racial and economic characteristics of its target

beneficiaries. We then use this analysis to identify a critical shift that we exploit as a natural experiment

to understand the effect of frames and strategies on resource distribution in a grantmaking setting. We

conclude with a discussion of the key contradictions demonstrative of the persistent processes

underpinning inequality even as espoused intentions change. This account contributes to institutional

theory and the domain of elite interference in inequality by calling attention to the powerful

connections between the promotion of marginalized concerns and the taken-for-granted components in

a field that protect institutional arrangements over time.

Elite Organizations, Inequality, and Higher Education



Although sociologists have long been interested in studying elite mobilization, there is limited

research concerned with educational inequality that explicates how elites working to ameliorate social

problems do so within existing frameworks of acceptable paths toward justice (Brandtner, Bromley, &

Tompkins-Stange, 2016; Quinn, Tompkins-Stange, & Meyerson, 2014; Wooten, 2016). Even less is

known about how elites’ orientations towards issues of race and inequality affect the outcomes of their

mobilization (Kelley & Evans, 1993; Skrentny, 2006). Given their primary role as organizations that wield

resources and a public platform to bolster legitimacy, grantmaking organizations can be understood as

elite actors embedded in a broader organizational field of higher education—that is “a community of

organizations that partakes of a common meaning system and whose participants interact more

frequently and fatefully with one another than with actors outside the field” (R. Scott, 1995, p. 96).

We use neo-institutional theory as a lens for understanding how such actors in a field draw on

and contribute to the constant reenactment of a common set of beliefs and structures, which are

referred to in this literature as “institutions.” To define institutionalization, we draw on Jepperson

(1991) (see also, Colyvas & Anderson, under review; Colyvas & Jonsson, 2011) who argues that a “social

order or pattern” is institutionalized if it is “chronically reproduced” by “self-activating social processes”

(p. 145).. Institutions reproduce themselves by determining the rules, norms, and standards taken for

granted in a field (Jepperson, 1991; Zucker, 1987). They are durable because they provide a set of

common meanings that facilitate or discourage patterns of action (Kim, Colyvas, & Kim, 2016).

It is common to imagine institutions as some immutable, externalized set of policies. Instead,

institutions inhabit or live in the cognitive and cultural constraints taken for granted by the actors in the

field (Meyer & Jepperson, 2000), and they are reproduced via embedded modes of incentive or reward

for enacting these taken-for-granted practices. For example, institutional scholarship identifies

legitimacy as a core feature of institutionalized structures (DiMaggio & Powell, 1983). This idea is linked

to the notion of taken-for-grantedness—the observation that institutions can construct and constrain



the courses of action seen as possible or legitimate (Colyvas & Powell, 2006; W. R. Scott, 2013).

Grantmakers looking to create change in an organizational field face the daunting task of simultaneously

being inhabited by and challenging the extant institutional arrangements.

While grantmakers often interrogate the success or failure of individual programs meant to

benefit people of color and the poor, the process by which grantmakers themselves shape and select

such programs goes unexamined. For example, the majority of grant resources fund and legitimize

inequality work at better resourced and more prestigious organizations (Kelly & James, 2015), but these

organizations serve only a fraction of the minoritized2 populations in the U.S. However, these

organizations possess key markers of legitimacy (e.g., research, rankings, resources) in the field of higher

education (Bastedo & Bowman, 2010; Colyvas, 2012; Espeland & Sauder, 2007). By awarding preference

to these types, grantmakers enact a form of institutionalized inequality whereby organizations that

serve the greatest proportion of minoritized students are also the most poorly resourced (DiMaggio &

Powell, 1983; Powell & Colyvas, 2008). This disconnect is one example of the many ways policies

ostensibly targeting minoritized populations can still benefit dominant groups (Dumas & Anyon, 2006;

Philip, Bang, & Jackson, 2018; Schneider & Sidney, 2009).

From an organizational perspective, relatively prestigious universities are a homogenous slice of

the larger field, particularly in terms of the demographics they serve (e.g., age, race, class), the resources

at their disposal (e.g., endowment), and their prestige (e.g., U.S. News and World Reports rankings,

Carnegie Classifications). This concentration of grant resources to a homogenous group in a diverse

population of colleges and universities has its drawbacks. First, U.S. higher education is a field where

non-elites colleges already mimic elite colleges in efforts to gain legitimacy and maintain accreditation

(DiMaggio, 1997; DiMaggio & Anheier, 1990; DiMaggio & Powell, 1983; Newman & Cannon, 1971). The

2 We refer in this paper to populations traditionally called “underserved” or “at-risk” (e.g., people of color,

low-SES populations) as “minoritized.” The term minoritized underscores minoritization as a socially constructed

act carried by social structures and interactions (see Conchas, Gottfried, Hinga, & Oseguera, 2017).



processes that institutionalize racial and class-based stratification in higher education are radically

different in a community college—an organizational type that serves more minoritized students than

any other sector—than at elite or even middle-tier universities. A wealth of literature points to the need

to develop and validate educational innovations in ecologically relevant contexts (Gutiérrez & Jurow,

2016; Lee, 2009; Lee, Spencer, & Harpalani, 2003; Nasir, Rosebery, Warren, Lee, & Sawyer, 2006;

Orellana & Bowman, 2003). In other words, existing research tells us that an educational intervention

designed in the context of an elite, wealthy, and predominantly White institution will not translate or

scale to a poor or predominantly minority serving institution.

Moreover, institutional theorists posit that while experimentation, like that afforded by grant-

funded programs, may be an important part of institutional change, not all actors are equally likely to

experiment in ways that will disrupt the status quo (Clemens & Cook, 1999; Phillips & Zuckerman, 2001).

Experimentation that leads to change is likely to come from groups that are marginalized by or do not

benefit from the current institutional arrangements (Clemens & Cook, 1999; Leblebici, Salancik, Copay,

& King, 1991). Conversely, groups or organizations that largely benefit from existing institutional

arrangements will be the least likely to challenge these arrangements (Phillips & Zuckerman, 2001). In

short, organizations marginal to the political system, or organizations with lower legitimacy, are denied

the benefits of current institutional configurations and thus have fewer costs and greater incentives to

experiment with alternative models as a way to gain access to capital (Clemens & Cook, 1999; Lounsbury

& Crumley, 2007; Schneiberg, 2005; Schneiberg & Lounsbury, 2008). Applying these predictions to the

postsecondary field suggests that prestigious universities are less likely to innovate in ways disruptive to

existing configurations as they benefit from them in terms of rankings, status, and reputation. In

contrast, a community college with little prestige or resources derived from reputation has more to gain

from experimentation that could lead to new measures of success. However, it is unclear under what



conditions grantmakers, many of whom are socialized in the field itself, are led to invest in the least

legitimate organizational types.

Policy Frames as a Strategy for Disruption

Even under the auspices of addressing “equity” some policy frames authorize actors to award

resources to the most “qualified” recipient (meritocratic distribution), while others push actors to

award resources based on need (compensatory redistribution) (Berrey, 2015; Espinoza, 2007; Jencks,

1988). As such, adopted definitions of equality at the societal and organizational levels are important

variables in social reform.

Policy problems are not “social fact awaiting discovery” (Coburn, 2006, p. 343); they are social

constructs reflective of the intellectual work and frames of elite groups (Harper, 2012; Kim et al., 2016;

Miksch, 2008; Schuman, Steeh, Bobo, & Krysan, 1997). The interdisciplinary literature on frames

provides analytical leverage. Grantmaking organizations and the individuals within them, develop

strategies in the context of a particular problem frame. Organizations engage in problem framing, or the

assignment of meaning to relevant events and conditions in ways that mobilize people, resources, and

policies, to support their vision and their promoted responses to a social condition (Benford & Snow,

2000; Pedriana, 2006; Snow & Benford, 1988; Snow, Benford, McCammon, Hewitt, & Fitzgerald, 2014).

Frames operate to cognitively and culturally focus actions on or exclude from vision specific social

problems and limit policy responses to a set of taken-for-granted understandings (Béland, 2009; Béland

& Cox, 2010; Benford & Snow, 2000; Gray, Purdy, & Ansari, 2014; Hand, Penuel, & Gutiérrez, 2013;

Snow et al., 2014; Surel, 2000).

We can operationalize these concepts more precisely pulling from the cultural sociology and

social psychology literature on cultural frames and diversity ideologies, which we argue amount to

frames for interpreting and responding to inequality. In both literatures there are two empirically

examined ideological frames: color blindness and diversity or multiculturalism. Color blindness is “the



belief that racial group membership should not be taken into account, or even noticed—as a strategy for

managing diversity and intergroup relations” (Apfelbaum, Norton, & Sommers, 2012, p. 205) and is the

most common stance taken by Whites (Apfelbaum et al., 2012; Rattan & Ambady, 2013; Stephens,

Fryberg, Markus, Johnson, & Covarrubias, 2012). The color-blind approach is the de facto ideology

driving discourse and policymaking in most domains (Apfelbaum et al., 2012; Bonilla-Silva, 2013). Color-

blind ideological frames are associated with a range of socially harmful outcomes including insensitivity

to blatant acts of discrimination and the distribution of resources and benefits to Whites (Plaut, Thomas,

& Goren, 2009; Purdie-Vaughns, Steele, Davies, Ditlmann, & Crosby, 2008; Rattan & Ambady, 2013). The

color-blind frame also effectively props up resistance to investments in race-based policies to ameliorate

inequality, like busing or affirmative action (Feagin, 2006; Schuman et al., 1997; Sears & Henry, 2005).

In contrast, multiculturalism is “an approach to diversity in which group differences are openly

discussed, considered… even highlighted” (Apfelbaum et al., 2012, p. 207) and in some instances

considered as things to celebrate (Berrey, 2015; Rattan & Ambady, 2013). Multiculturalism affords some

social benefits including contributions to less hostile environments for people of color and improving

assessments of discrimination (Apfelbaum et al., 2012; Todd, Hanko, Galinsky, & Mussweiler, 2011). This

perspective can be linked to feelings of exclusion, threat, or alienation among White individuals that can

negatively affect their likelihood to value or devote resources to diversity-focused initiatives (Norton &

Sommers, 2011; Rattan & Ambady, 2013). While the multicultural frame, historically, is seen as a

product of the civil rights movement, this frame normalizes the celebration of diversity, but has not

been shown in the literature to support preferences for structural solutions to patterned social

inequality (Berrey, 2015; Bonilla-Silva, 2013; Hirschman, Berrey, & Rose-Greenland, 2016).

Color-blind and multicultural ideological frames have defined the U.S. social policy field in

relation to diversity in the last half century, and assessed on their outcomes they are comparable in

their maintenance of meritocratic rather than a redistributive investments. Both positions advocate for



things like the equality of opportunity in education as the absence of discrimination (color blindness)

and in some cases that we should do so because everyone, including Whites, benefit from diversity

(multiculturalism) (Berrey, 2015; Hartmann, 2015). However, this is not the same as an ideology driven

by a moral or political conviction about the need to proactively eliminate inequalities (Bensimon &

Bishop, 2012; Hartmann, 2015; Hild & Voorhoeve, 2004; Warikoo & Novais, 2015). This may explain how

policies targeting minoritized populations are often still used to benefit dominant groups (Berrey, 2015;

Harper, 2012; Hartmann, 2015; Philip & Azevedo, 2017; Schneider & Sidney, 2009; Umbricht, Fernandez,

& Ortagus, 2015; Yosso, Parker, Solorzano, & Lynn, 2004).

In the current policy discourse, we identify a third, emergent ideological frame, often referred to

as “equity,” or “social justice,” which we will refer to as a race and class justice frame (Berrey, 2015;

Philip & Azevedo, 2017). The racial and class justice frame takes a structural approach that “foregrounds

the unequal power relationships between racial groups in society... [the] normative consequence of this

frame is that individuals should actively resist the racial ideologies and injustices that they perceive.”

(Warikoo & Novais, 2015, p. 861). This perspective, held by few Whites, is not limited to establishing

freedom from active discriminations and the benefits to the dominant group of multiculturalism. This

frame invokes a responsibility among those in power to identify historical traditions of oppression and

to offer proactive solutions that have causal effects on inequality (Bonilla-Silva, 2013; Hild & Voorhoeve,

2004; Warikoo & Novais, 2015; Yosso et al., 2004). However, many argue that such a framing is

threatening to the privileges of the dominant group and will only get taken up when justified in terms of

the benefits it offers to dominant classes, a phenomenon known as interest convergence (Bell, 1980;

Philip et al., 2018; Vossoughi & Vakil, 2018; Yosso et al., 2004).

While this literature speaks to frames’ effects on political preferences or discriminatory

practices, it does not speak systematically to how we know issues of race and class affect policy frames

in particular ways (Brown, 2013). Policy design theory (Schneider & Ingram, 1993) provides a final layer



to our predictions by directing attention to “how constructions of groups, problems and knowledge then

manifest themselves and become institutionalized into policy designs, which subsequently reinforce and

disseminate these constructions” (Schneider & Sidney, 2009, p. 106). While groups associated with

positive constructions (e.g., White, middle class parents) tend to receive policies with high levels of

discretion and strong provisions, groups associated with negative constructions (e.g., poor people of

color) receive policy designs that distribute burdens, have lesser benefits, and carry “low levels of

discretion [and] long implementation chains (some of which flow to advantaged groups)” (Schneider &

Sidney, 2009, p. 107). This theory demonstrates that conceptions or beliefs about the target population

of a given policy is likely to activate other frame elements in patterned ways. In other words, the valence

and power of the target beneficiaries will relate to particular policy designs in terms of the magnitude of

benefits, levels of freedom, creativity, and surveillance directed to beneficiaries.

Based on this combination of literature on framing, policy design and the effects of diversity

ideologies, in the context of this study we predict the following:

Hypothesis 1a: When a color-blind or multicultural ideology is used in FIPSE’s policy frame: 1)

The organization’s priorities will emphasize taken-for-granted values in the field (e.g., learning,

technological advances, organizational improvement), and 2) Grants distribution will feature high levels

of freedom for creativity, lower surveillance, and shorter implementation chains. In other words, if the

contradiction between the liberal aims of U.S. higher education and the patterned inequalities in the

field is not directly challenged, the existing value system will be upheld and highlighted for

preservation—to be more of what the institution already is.

Hypothesis 1b: When a racial and class justice ideology is used in FIPSE’s policy frame: 1) The

organization’s priorities will explicitly justify its work in terms of interest convergent goals, i.e., the

expected macro-level benefits to the dominant group of addressing the needs of minoritized groups

(e.g., reduced crime or unemployment), and 2) grants distribution will feature low levels of freedom for



creativity, higher surveillance, and longer implementation chains. In other words, if the contradiction

between liberal aims of the institution and patterned inequalities in the field is directly challenged, the

frame will need to justify this threat to the existing value system by pulling from some other value

system acceptable to dominant actors.

Hypothesis 2a: When a color-blind or multicultural frame is used in FIPSE’s policy frame, grant

funds will be disproportionately directed toward more prestigious and well-resourced colleges that

serve a larger proportion of non-minoritized students. These organizations possess key markers of

legitimacy in the field and will thus be rewarded as worthy of investment, but they are the least likely to

experiment in ways that challenge institutional arrangements.

Hypothesis 2b: When a racial and class justice ideology is used in FIPSE’s policy frame, it will

favor the distribution of resources to less-prestigious and resourced colleges that serve a larger

proportion of minoritized populations. The preference in the frame for minoritized groups will push

funding to organizational types that serve these communities but who would otherwise lack legitimacy.

These types are also the most likely to experiment in ways that challenge institutional arrangements.

Methods & Setting

This analysis focuses on FIPSE’s operations and its funded recipients (1995-2015) using a mixed-

method, longitudinal approach. FIPSE’s charge, per its original legislative mandate, was to disrupt

postsecondary educational inequalities by investing in projects that create “innovative reform and

expand education opportunities to underrepresented groups” (Higher Education Act of 1965, as

amended, 2008). Legislative documents and in-depth interviews have also demonstrated that FIPSE had

a uniquely flexible statutory authority to behave like a private foundation and allow the agency to

respond to innovative avenues for educational change, thus allowing this case to lend insights across

multiple grantmaking domains. FIPSE’s organizational features and level of political autonomy remained

steady from its founding through the very early 2000s. Under the Bush administration, Congress



introduced an influx of non-competitive, earmarked grants into FIPSE’s annual budget allocation. This

Congressional interference reduced FIPSE’s political autonomy and the scope of its competitive

program.

This study took, as its starting point, the highly public shock to the agency’s policy frame

introduced by the Obama administration, called “First in the World” (FITW). In 2013, the Obama

Administration announced FITW as a comprehensive reframing of this federal program. FITW was

intended to reposition the fund to focus more squarely on “at-risk” student success and on moving the

U.S. back into a position as “first in the world” for producing college graduates and a first-rate workforce

with projects that boost “postsecondary access, affordability and completion for underrepresented,

underprepared or low-income students at institutions across the country” (U.S. Department of

Education, 2014). This shift ended both the practice of congressional earmarking and the decades-long

Comprehensive Program, FIPSE’s continuous flagship program.

FITW acts as a natural experiment relevant to framing and institutional theories because the

treatment was largely limited to the implementation of a new policy frame. FIPSE is an apt setting for

this study for three key reasons. First, this agency’s value proposition focused on creating heterogeneity

in institutional forms within the field over time; meaning, FIPSE sought to disrupt the trend among non-

elite colleges and universities to mimic elites regardless of actual benefit to students.3 Second, FIPSE’s

work spans multiple eras of postsecondary improvement including the era preceding court suppressions

on affirmative action policies, the rapid and drastic expansion of college access that occurred in the

1990s, and the emergence of the college completion agenda that came to the fore in the 2000s. Third,

from its founding in 1973 through its shuttering in 2018, FIPSE’s legislative mandate was to disrupt

inequalities in postsecondary education through investments in innovation. This constant allows us to

3 This intention is well-documented in FIPSE’s archival materials, including Newman & Cannon's (1971)

Report on higher education, which is considered FIPSE’s founding document.



more precisely test and analyze the effects of variation in frames over time. Table 1 provides summary

statistics of FIPSE’s grantmaking history from 1995-2015. This table illustrates the overall growth in

FIPSE’s grantmaking portfolio and shifts in its grantmaking strategy as it varied the number and size of

grants over time.

Methods for Tracing the Changing Frames and Policy Designs at FIPSE

In order to trace the mechanisms and the qualitative features of FITW as a framing and

organizational change, we have collected an archive of over 800 documents from across FIPSE’s 45-year

history. Our analysis for this paper focuses attention on the annual grant guidelines (1995–2015) which

includes 92 documents collected from university libraries from across the U.S., the National Library of

Education in Washington, D.C., the Federal Register, and the Grants.gov federal database. We chose this

timeframe to analyze the pre-trend ahead of the Obama-era change, as well as to align with the analysis

of quantitative administrative records. We limited the scope to grant guidelines, omitting congressional

hearings, internal reports, and other types of documents in favor of a focus on documents representing

the contemporary, public-facing communication about FIPSE’s procedures and priorities. These priorities

are also the template against which individual program officers “score” grant applications. As such,

annual guidelines represent both the external cue to the field for what the agency is willing to fund, and

the internal tool used to identify worthy projects. This combination makes a longitudinal set of grant

guidelines an ideal dataset from which to deduce persistence and change in the agency’s policy frame

over time.

We employed a deductive content analysis process (Miles, Huberman, & Saldana, 2013)

isolating and longitudinally comparing the key elements of this agency’s espoused frame. Using Benford

& Snow’s (2000) model for frame analysis, we coded for the following frame elements: target

beneficiaries, the identification of social problems (diagnoses), the promoted solutions (prognoses), and

the metrics that signal success. We analyzed the resulting codes for their persistence and change using a



chronological data matrix (Miles et al., 2013), and then examined to what extent the diagnostic and

prognostic elements amplified or problematized established arrangements within the higher education

field. Our findings illustrate the results of this analysis using exemplars taken from before and after the

FITW change.

Methods for Measuring the Effects of Frame Change

The qualitative analysis of FIPSE’s changing frames reveals that the agency abruptly moved from

espousing a color-blind and multicultural frame in its priorities, to a frame more squarely focused on

racial and economic justice under the Obama administration. In the models that follow, we measure the

effects of this switch in framing and test hypotheses 2a (when a color-blind or multicultural frame is

used in FIPSE’s policy frame, grant funds will be disproportionately directed toward more prestigious

and well-resourced colleges that serve a larger proportion of non-minoritized students) and 2b (when a

racial and class justice ideology is used in FIPSE’s policy frame, it will favor the distribution of resources

to less-prestigious and resourced colleges that serve a larger proportion of minoritized populations). In

order to test these hypotheses, we examine two sub questions. First, prior to the introduction of FITW,

did FIPSE disproportionately allocate its resources to either White-serving and/or elite (i.e., prestigious

and well-resourced) colleges and universities? And second, did the FITW framing change have a causal

effect on grantmaking outcomes such that minority-serving and less-elite institutions receive greater

benefits? In this study, two correlated constructs are used to differentiate various types of colleges and

universities: the populations they serve (whether minoritized based on race or class) and the degree of

prestige and resource capacity they possess as in organizational type.

Identification strategy. A new grantmaking frame could affect funding outcomes by one of two

mechanisms, or a combination of the two mechanisms. The grant guidelines could signal new

preferences to the field, encouraging a new set of organizations to apply for funding. Alternatively, this

frame could prime different reviewer preferences and set in motion different processes for selecting



preferred projects, thus changing the scores allotted to applications. Outside of qualitative reports from

FIPSE’s agents, which indicate that it was likely a combination of these two mechanisms, the

quantitative data to measure these mechanisms separately is unavailable. In the absence of these data,

we measure the net effect of the FITW framing change.

Making a causal argument about whether a new policy frame has an effect on policy outcomes

is challenging given the many endogenous factors that affect grantmaking organizations. For example,

we could compare the beneficiaries of one grant program to another. However, factors endogenous to

the two programs, like the groups they historically serve based on some founding factor or the

preferences of individual staff, could introduce bias. One could also look at a single grantmaking

program before and after it changed its policy frame. Endogenous to this change could be turnover in

staff, new political preferences in the governing party, or changes in the larger ecology of organizations

applying. A difference in difference design allows us to control for the differences across the two

programs by looking at changes over time. This approach also allows us to control for factors that

change over time besides the policy in question. For example, we can control for broad political

preferences or presidential administration by measuring the difference before and after the policy

change in comparison to a program unaffected by the specific policy change that is also subject to the

same time variant, environmental factors.

To answer these questions, we used a Difference-in-Difference-in-Difference (DDD) strategy that

estimates the causal effect of this policy change on grantmaking outcomes in terms of the distribution of

funds to different organizational types, with FIPSE acting as the test group and another federal agency

that awards grants to colleges and universities, TRIO Student Support Services (SSS), as a comparison.

For the purpose of this analysis, we included grants made to colleges and universities. The comparison

group is meant to measure the changes in applicant behavior and funding decisions that would have

happened over time to FIPSE if FIPSE had not instituted the FITW change. SSS is another federal grant



program founded in the late 1960s with a similar mission and target population. The policy change in

question—FITW—was not applied to SSS and in general, SSS’s stable policy framing arguably insulates it

from ideological pressures given its relatively constrained mission. However, SSS shares with FIPSE the

same context in terms of trends in funding levels, political administration changes, etc. These are

among the confounding factors we control for using the DDD design.

The intuition behind this strategy is the same as the more widely used difference in difference

(DD) design, which measures the effect before and after a change of a treatment on a group relative to

the changes in an untreated comparison group. We first conduct a DD to measure change in outcomes

before and after the policy change for both grant programs. However, if the comparison group—in this

case SSS—is suspected to share some difficult-to-control determinants, an additional difference can be

introduced, thus controlling for factors that could bias the average treatment effect (Berck & Villas-Boas,

2016). In the models described in this paper, a third variable representing one of nine key institutional

characteristics, is used to control for these factors. For example, one of these institutional characteristics

is a dummy variable for whether a college is a Minority Serving Institution (MSI) (defined by serving 50%

or more students of color in a given year). We use the DDD framework to measure the differential

effects of FITW on MSI v. non-MSI institutions. The intuition is comparable to a study that uses changes

in males’ outcomes in a population as a comparison group for a treatment that should only affect

females. This puts the effects in context not only of a comparison grant program, but the impact on MSIs

relative to the non-MSI population which accounts for changes to those populations that are not caused

by other factors relevant to the mechanisms under study.

Due to SSS data availability, we examine data on pre-FITW trends in the outcomes of interest

among these two agencies from 1995 forward. We begin analysis in 2004 to eliminate the influence of

the introduction of congressional earmarking in FIPSE’s grantmaking portfolio. This earlier policy change

is used as a sensitivity check as described later in the paper. While each of our main analyses focuses on



one of nine institutional characteristics, described in full in the next section, we will explicate the model

using a generic variable for these characteristics (“CHAR” below) as an example. The model is as follows,

In this equation, the dependent variable Yit is the dollar amount an individual college or

university received in a given year from either of the two grant programs. If it received no funding at all,

it receives a zero. FIPSE takes a value of 1 if the record is part of the FIPSE half of the data set and 0 if it

is in the SSS half of the dataset. CHAR takes a value of 1 if it meets the criteria for the institutional

characteristic. Post takes a value of 1 if the condition “after the policy change” is met, γ are sector fixed

effects to control for time-invariant characteristics by organizational sector (e.g. public v. private, four-

year v. two-year colleges), α are time fixed-effects to account for general inflation and changes in grant

funding availability (e.g. under different administrations), and ε is an error term. The subscript i indicates

the specific institution, and t indexes time measured in five-year windows. We estimate this regression

using clustered standard errors at the organizational level. The coefficient of interest here is β6, which

measures the causal effect of the policy on a FIPSE grantee characteristic relative to the comparison

group and to grantees without this characteristic. The identifying assumption is that these

characteristics would not have changed at differential rates between FIPSE and the SSS program in the

absence of the policy change.

Data. The independent variables in this analysis fall in three categories: institutional

characteristics, treatment period, and grant program (See Tables 2-4 for a list of and original sources of

all variables). Each of the regressions in the findings section focuses on one of nine institutional

characteristics. These characteristics fall into one of two constructs by which we can understand the

variation in the profile of funded organizations. These constructs are student population variables and

organization-level prestige or capacity variables.

Yit= β0+β 1(FIPSEit)+β 2(FIPSEit*Postt)+ β 3 (CHARit) + β 4 (CHARit*Postt) +

β 5 (CHARit*FIPSEit)+ β 6 (CHARit*FIPSEit*Postt) + αt + γi + εit



Student population variables measure the representation of particular populations, specifically

in terms of race and class at each college or university (see Table 2). These variables were drawn from

the Integrated Postsecondary Education Data System (IPEDS), which collects data annually about

students, staff, faculty, finances, admission and graduation rates, and more from every college or

university eligible to receive federal aid. We downloaded these annual data from the IPEDS database

from 1980 – 2016. Using Stata 15, we cleaned and matched these records by year, using the time-

invariant unique identifier assigned to organizations within the IPEDS system. We used multiple record

matching techniques to link these records to FIPSE and SSS data using institution name, zip code, and

state variables. Where time-invariant data were missing in certain records (e.g., public v. private status),

we imputed using the most recent non-missing record in the dataset. Where time-variant data were

missing, we imputed an average value by sector and year (e.g., the average for other community

colleges in that year).

Organizational prestige and capacity variables measure the classification (highest degree

offered), relative ranking of the institution (US News and World Reports), and existing wealth

(endowment and instructional spending variables) available to the institution to carry out its mission

(see Table 2). Measures for existing wealth—endowment and instructional spending—were drawn from

IPEDS and followed the procedures outlined above. Variables measuring classification were drawn

directly from the Carnegie Classification System, a dataset maintained by Indiana University originally

published in 1973, with rankings and measures updated in 1976, 1987, 1994, 2000, 2005, 2010, and

2015 to reflect changes among colleges and universities. This dataset includes the unique IPEDS

identifier and was easily matched. Given that the Carnegie Classifications have varied over time, we

simplified categories so that measures used in these models have parity over the scope of this study. For

example, in its latest iteration, doctoral institutions are split into multiple levels of research activity. We

grouped these into a single category which reflects its 1994, 2000, and 2005 indices. Variables for



relative ranking were drawn from longitudinal data drawn from US News and World Reports

documenting the top 50 ranked universities and top 50 ranked liberal arts colleges (total 100 per year)

for every year since 1983. We downloaded these data, which also contained the IPEDS unique identifier

from Dr. Andrew Reiter of Mount Holyoke College’s shared data page.

The dataset is organized by institution and year, with each unique institution-year combination

appearing twice in the dataset. One record documents the FIPSE grant the organization received in

dollars that year (it receives a “0” if no grant was awarded), and the other record documents the SSS

grant the organization received in dollars that year (it receives a “0” if no grant was awarded). A dummy

in both records indicates whether the record occurs before or after the “treatment” period (i.e., the

implementation of FITW) based on the year in which the grant occurred (before or after 2013).

Summary statistics for the organizational variables of interest for all colleges and universities

represented in the IPEDS universe are presented in Table 5. The table breaks out means and standard

deviations for selected variables in the years 2004-2015 for all colleges and universities, as well as for

subpopulations that received either FIPSE or SSS grants in these periods. The first six columns provide

summary statistics for these three populations in the pre-period (prior to FITW). The next six columns

provide summary statistics for these three populations in the post-period (after FITW).

Findings

In the sections that follow we will demonstrate how, after decades of employing a color-blind

and multicultural frame, a policy change abruptly shifted FIPSE’s policy frame to favor racial and class

justice. As FIPSE’s grantmaking frame toward equity shifted, so did elements of its strategy and policy

design in three key ways. First, FIPSE began to promote a restricted set of prescribed and pre-tested

modes of change, rather than their earlier strategy focused on innovative field-driven projects. Second,

FIPSE abruptly shifted to prioritize high levels of accountability and surveillance in the form of

experimental and quasi-experimental evaluation requirements using market-based outcomes (e.g.,



graduation rates). And third, FIPSE shifted from making many small to fewer, large grants. Using a DDD a

model of causal inference, we find this change had a positive effect on the delivery of grant dollars to

institutions that serve minoritized students (as measured by race and income), which comes after

decades of underservice to these organizational forms. Despite its espoused interests, this shift in

resources did not favor the most marginalized organizational types that serve the majority of the

nation’s poor students and students of color (e.g., minority-serving community colleges, lower ranked

and poorer institutions). Taken together, we find that as the beneficiaries shifted away from non-

minoritized populations, FIPSE eliminated the creativity, freedom, and low-levels of accountability

afforded to grantees. These findings demonstrate how, even as FIPSE used its policy frame as a strategy

for disruption, with causal consequences on resource distribution, the mechanisms that support

inequality changed, thus leaving intact structures of benefits and burdens likely to perpetuate

inequality. In the sections that follow, we will demonstrate these findings in detail, beginning with the

archival analysis establishing the content of this critical policy frame change and then moving into the

causal estimates of the impacts of this frame change derived from our DDD analysis.

An Abrupt Change to an Agency’s Racial and Class Policy Frame

Rather than a gradual change over time or an inconsistent policy approach, FIPSE moved under

the Obama-era change from a fixed frame consisting of both multicultural and color-blind elements, to a

racial and class justice orientation. Figures 1 and 2 visually summarize how this framing stance

corresponds to the broader transformation in the policy’s framing and policy design. The text in the

green boxes of both figures demonstrate how changes in policy frames regarding the target population

correspond to changes in problem diagnoses and promoted solutions. Under the racial and class justice

condition, FIPSE began to exclusively motivate its work in relation to problems of broad, American

economic competitiveness. FIPSE’s promoted solutions also changed from a flexible invitation to

propose multiple types of innovation to a limited menu of educational remediation tactics. Similarly,



critical elements of the policy design also shifted as demonstrated in the orange boxes of both figures,

favoring increased accountability and surveillance demands, an increased prescriptiveness in terms of

how FIPSE dictated its preferences to the field, and a decrease in the number of potential beneficiaries.

We will explicate these findings in detail using exemplars in the sections that follow.

A consistent colorblind and multicultural frame. Analyzing the published guidelines from the

1990s and 2000s prior to the introduction of FITW, we find that when issues of inequality are addressed,

the agency consistently positions its project in relation to “diversity” or opportunity “gaps.” However,

these concepts are not a central or driving feature in the agency’s argument to the field about the types

of grants and innovations it intends to fund. As demonstrated in Figure 3, which is an excerpt of FIPSE’s

1995 grant guidelines, the motivating theme, rather than inequality or justice, hinges around

“innovation.” Although that term is not explicitly defined, the examples offered in the documents

include foci such as technological change, engaged pedagogy, and new models for measuring learning.

These foci operate without reference to concerns about inequality (despite the agency’s statutorily

established purpose). Instead, this text emphasizes the need to amplify the educational strengths in

which the U.S. was already, purportedly, the world leader. This trend was further confirmed in

interviews with former program officers who, above all in this period, report being concerned with

finding and providing the “venture capital” to the field for “creativity and experimentation... coming

from the field” and indeed, to “make them famous.” This finding supports the prediction put forth by

hypothesis 1a (when a color-blind or multicultural ideology is used in FIPSE’s policy frame, the

organization’s priorities will emphasize taken-for-granted values in the field (e.g., learning, technological

advances, organizational improvement), given the peripheral nature of minoritized identities in FIPSE’s

pre-FITW documents.

In this era, FIPSE enacted a problem frame that is open to but not motivated by promoted

solutions to reduce racial or class inequalities. For example, the 1995 guidelines specify eight invitational



priorities to the field. According to federal guidelines, an invitational priority signals a general interest to

the field, but it is neither a requirement nor a preference in the funding agency. In fact, in this period,

FIPSE solely published invitational, rather than absolute priorities, in order to be what actors referred to

as “field-driven” in their approach to innovation. Only one of these eight priorities refers at all to a

target population. In this priority, illustrated in Figure 4, labeled “Access, Retention, and Completion”

the importance of educational access and college completion is described. Within this description there

is an emphasis given to “low-income and underrepresented minority students.” This emphasis illustrates

that inequality concerns are not excluded from the agency’s frame. However, this identify-specific

element is positioned as one of multiple, optional priorities, the rest of which focus on color-blind

educational pursuits and systemic values such as learning quality or “technological advancement and

innovation.”

Over ten years (and a presidential administration) later in 2006, this framing is consistent. As

demonstrated in Figure 5, an excerpt from the 2006 guideline text, there is a passing reference—this

time to “increasing diversity”—to the issue of the agency’s target population. This emphasis is part of a

list of social concerns also including “the dramatic rise of information technology and the “renewed

demand for accountability.” As in 1995, this text provides a single reference to an issue that may or may

not be related to race or class embedded in a larger list of invitational priorities. This finding is

consistent with the hybrid color-blind and multicultural frame mobilized in the 1995 text.

This use of “diversity” without a specified policy preference may serve a legitimizing purpose

(Berrey, 2015; Bonilla-Silva, 2013). The agency is supposed to attend to these issues based on explicit

references in its founding legislation, but in this text, the problem, as it related to higher education, is

not driven by or centered on reimagining institutional arrangements around issues of race, class, or

identity. This feature is a hallmark of multicultural framing approaches, which are quick to celebrate

diversity but typically do not address structural inequalities (Hartmann, 2015; Warikoo & Novais, 2015).



FIPSE’s symbolic moves align the agency with larger institutional concerns about inequality and changing

demographics. However, this frame does not obligate the agency to consider their grantmaking as a way

to direct resources to minoritized populations. Furthermore, nowhere in this text is there a

demonstrated emphasis on or guidance relevant to requirements for empirical evidence or evaluation

methods, a fact thrown into relief by the next exemplar.

A new, justice-oriented frame emerges. In the post-2013 documents, a new perspective

emerges that explicitly places minoritized populations at the heart of FIPSE’s prognostic and diagnostic

frame. In this period, after the initiation of “FITW,” named inequalities drive the agency’s argument to

the field. As demonstrated in excerpts from the 2015 and 2014 grant guidelines (Figures 6 and 7,

respectively), FIPSE’s driving concern is motivated not by a general interest in diversity as part of a list of

social issues, but rather by a distinct concern for economic well-being for which college completion is

used as a proxy, and an appeal to international competitiveness embodied in a goal to “lead the world”

in the proportion of citizens with a college degree. Validating hypothesis 1b (when minoritized identities

are central to a policy frame, an organization’s priorities will explicitly justify their work in terms of

expected macro-level benefits to the dominant group of addressing minoritized group needs), this move

appeals to concerns for American competitiveness that ultimately benefit all groups. In summary,

FIPSE’s frame changed abruptly under FITW, moving from a mixture of color-blind and multicultural

framings to an identity-specific racial and economic justice frame.

In the post-FITW texts demonstrated in Figures 7 and 8, FIPSE moves toward service to

minoritized groups by appealing to the ultimate concern of American economic competition. In this text

the agency argues that demographically, the nation will never again achieve the same level of

dominance if the success of minoritized students is not drastically improved. In doing so, specific

organizational forms—those that serve a majority of such students—are called out as particularly

valuable.



An excerpt from the 2014 grant guidelines, shown in Figure 8, exemplifies how the specificity

and detail of the language regarding inequality changed from the pre-FITW period at multiple places in

the guidelines. Whereas earlier grant guidelines contained only passing references to “underserved

populations,” here, the agency offers greater specificity as it names “low-income, underprepared, and

underrepresented students,” and provides exposition on 1) why these populations matter in the scope

of higher educational processes, and 2) offers specific metrics to which winning projects must attend

that will be measured by a panel of evaluation experts FIPSE contracted to assure that willing proposals

pass muster in terms of evidentiary backing. These metrics are largely focused on market-based

outcomes like the economic value of greater college completion. Post-FITW, FIPSE’s moves to name a

problem, identify its source, and specify a necessary change are a precursor to how this new frame

emerges in the organization of the rest of the text. This new frame conveys to the field that FIPSE is now

motivated by a concern for addressing disproportionate educational success. This is most apparent in

the way FIPSE positions access or success for minoritized groups as an absolute priority, under which all

other priorities are organized. Ensuing priorities are essentially specific intervention strategies meant to

change traditional higher education functions, fulfilling in some way a larger vision of racial or economic

justice. Reiterating this contrast, in the previous era, FIPSE guidelines refrained from providing

restrictive intervention recommendations, opting instead to let the field shape the direction of

innovation from within. Again, this is what informants called a “field driven” response motivated by the

belief that existing leaders in higher education already knew where the field needed to go, they just

needed funding to get off the ground.

Policy design changes beyond the targeted beneficiaries. Critically, the rise of this racial and

class justice frame is coupled with a novel emphasis on evidence and performance metrics and more

restrictive design standards. FIPSE’s post-FITW grant guidelines provide strong mandates regarding

thresholds of evidence for all proposed interventions, and rigorous requirements for evaluation



planning. Similarly, rather than FIPSE asking the field for its best innovation ideas as in the pre-FITW

guidelines, FIPSE began under the new frame to dictate the best ideas to the field. The agency invited

applicants in these guidelines to test rather than generate strategies. This change in logic aligns with

informants who reported this as a time in which “building evidence” became a primary concern, as did a

more adversarial approach to grantmaking in which you “can’t be friends” with grantees, and you have

“to break some china to create change in higher education.” This approach is deeply different from the

“innovative,” “partnership” and “field-responsive” goals of grantmaking under the earlier FIPSE regime

where specific underserved identities were not emphasized. On one hand, this increase in surveillance

could signal FIPSE’s seriousness about making a difference for minoritized students. On the other hand,

the exponential increase in required surveillance under the FITW framing, also lengthens the

implementation chain of the grants, as predicted by policy design theory. In other words, more highly

trained applicants and expensive processes are required inputs for successful grant proposals than in

previous competitions.

Whereas ostensibly, underserved students were the target of this innovation-focused agency

from its first day of operation, in the fifteen years leading up to FITW, FIPSE did not emphasize the

importance of specific identities in its grant guidelines. FIPSE mobilized a new, identity-specific emphasis

using the neoliberal tactics common to the Obama Administration’s approach to policymaking: the new

FITW frame coupled issues of quantifiable college completion metrics among minoritized students with

broad economic concerns relevant to the prosperity of all Americans and immensely rigorous standards

of evidence and accountability. Indeed, the guidelines inextricably couple service to minoritized

communities with standards for experimental or quasi-experimental evaluation methods.

The Causal Effect of the FITW Frame and Policy Change on Grant Beneficiaries

We exploit the shift in FIPSE’s frame and promoted strategies established in the preceding

archival analysis as a natural experiment demonstrating the effect of frames and strategies on resource



distribution in a grantmaking setting. We begin by examining the relationship between the FITW framing

change and awards to institutions with a high proportion of minoritized students. These findings are

summarized in Table 6. We operationalize this in five ways, using (1) a dummy variable for whether or

not a college is a minority serving institution (MSI), which means 50% or more of enrolled students are

underrepresented minorities (Model 1); (2) a dummy variable for whether an institution is a historically

minority serving institution (HMSI), i.e., a Historically Black College or University or Tribal college (Model

2); (3) a dummy variable for whether an institution is in the top quintile within its sector (e.g., public

two-year college, private research university) for serving need-based Pell-grant students (Model 3); (4)

continuous measures of grant dollars delivered based on the percentage of Black student enrollment

(Model 4); (5) continuous measures of grant dollars delivered based on the percentage enrollment of

underrepresented minorities enrolled (Model 5); and (6) a continuous variable for the average size of

the need-based Pell grant delivered per student at that institution (Model 6).

The first row of regression Tables 6, 7, and 8 labeled “FIPSE” provides the baseline average grant

size, before the “post-period” or FITW program for institutions that receive a “0” for the tested

characteristic, relative to the SSS grant program that year. The second row labeled “FIPSE Grant*Post-

FITW” represents the average change in grant size after the FITW policy change for institutions that

receive a “0” for the tested characteristics under either grant program. The next row labeled

“Characteristic” represents the average effect of the tested characteristic on SSS (the comparison group)

grant size. The fourth row with results, labeled “Char*Post Period”, represents the change in award size

for SSS grantees after FITW for institutions possessing the key variable. The fifth row with results,

labeled “Char*FIPSE Grant” can be understood as the pre-trend relationship between institutions with

the tested characteristic and FIPSE funding. This row represents the correlated effect on FIPSE grant size

of possessing the key variable in the pre-period over or under the SSS control group. And finally, the

sixth row, labeled “Char*Post*FIPSE Grant,” which is the coefficient of interest, represents the effect of



the FITW policy on the size of grant awards given to institutions possessing the characteristic compared

to institutions without the characteristic. This increase is estimated relative to the increase in award size

in the SSS program for institutions possessing the characteristic compared to institutions without. We

control for time and sector fixed-effects in all models.

Causal Estimates Based on Student Population-Level Measures. Results reported in Table 6

support the predictions made in hypotheses 2a and 2b regarding changes in student populations

represented at funded colleges. Hypothesis 2a predicts that in periods in which color-blind or

multicultural frames guide the agency’s work and minoritized categories are not specified as necessary

beneficiaries, White-serving institutions will receive greater financial benefits. The pre-trend

demonstrates that prior to FITW, FIPSE was less likely to award funds to institutions that serve higher

proportions of minoritized students on all racial measures, including whether or not an institution was

an MSI (b= -4,668, p<0.01), an HMSI (b= -19,763, p<0.01), or a high-Pell serving institution (b=-6,110,

p<0.01), as well as the proportion of underrepresented minorities enrolled (b = -436.8 p<0.05), the

proportion of Black students enrolled (b = -710.4, p<0.05), and the average Pell grant award per student

as a proxy for service to low-income students (b= -0.304, p<0.01). Interpreting these coefficients, on

average an MSI, in any sector, received an estimated $4,668 less in FIPSE grant funds than a non-MSI in

the years prior to the policy change relative to SSS. Using continuous enrollment measures as an

alternate specification, if a university enrolled 100% Black students, it is predicted to receive an

estimated $710.40 less in FIPSE grant funds.

As predicted by hypothesis 2b in regard to enrolled populations, in response to the FITW

framing change, there is a causal, significant shift in favor of awarding grants to colleges that serve

minoritized populations (underrepresented minority and poor students) as measured by average grant

awards to MSIs (b = 14,942, p<0.01) and average grant award delivered to high-Pell serving institutions

(b=12,003, p<0.1), as well as on a continuous measure of grant dollars delivered based on the



percentage of Black student enrollment (b= 23,824 p<0.01), enrollment of students of color (b= 12,130

p<0.1), and average Pell grant per student (b= 1.205 p<0.01). The policy has nonsignificant effects on

HMSIs, although the magnitude of the coefficient is similar. Figure 9 illustrates the pre-trends and causal

effects of the FITW change on grant benefits awarded to MSIs and high-Pell serving institutions relative

to their counterparts (i.e., non-MSIs and low-Pell institutions). This figure demonstrates that FIPSE

consistently awarded less funding to MSIs relative to non-MSIs than SSS, and that FIPSE awards to MSIs

and high-Pell institutions were trending downward prior to an abrupt spike following the policy change.

Causal Estimates Based on Organization-Level Measures. The preceding analysis demonstrates

that the primary goal of the new policy frame was achieved—a shift toward awarding grant dollars to

colleges that serve more poor students and students of color. One might wonder if these effects are

merely the result of a radical shift across all beneficiary parameters and are not a response to the

observed frame change. In this section, we demonstrate how, if we measure other organizational

parameters including measures of capacity like endowment and instructional spending or prestige

measures like organizational type or US News and World Reports rankings, FIPSE’s funding pre-trends

are largely undisrupted. On one hand, this offers a falsification test of the main results, demonstrating

that these were not idiosyncratic changes to FIPSE’s investments. On the other hand, these analyses

offer evidence of a critical contradiction: FIPSE’s historic tendency to fund higher prestige, higher

capacity institutions that serve substantially less minoritized students does not change.

In Table 7, we move to examining the relationship between the FITW framing change and

awards to institutions with higher prestige and capacity. We operationalize prestige and capacity in six

ways: (1) a dummy variable for whether an institution has ever been in the US News Top 100 colleges

and universities (Model 7), a group that comprises only 167 institutions out of 8,000 unique institutions

that appear in IPEDS every year; (2) a dummy for whether the institution is classified as a doctoral-

degree granting institution in that year according to Carnegie Classifications (Model 8); (3) a dummy for



whether the institution is classified as an associate-degree granting institution in that year according to

Carnegie Classifications (Model 9); (4) a dummy for whether the institution is classified as a community

college (a public two-year college) (Model 10); (5) a continuous measure of the endowment wealth

possessed by that institution (Model 11); and (6) a continuous measure of the dollars spent per student

on instructional costs by that institution (Model 12).

Under hypothesis 2a, we predict that prior to FITW, FIPSE would favor higher prestige and

better resourced organizations. The results provide support for this hypothesis showing significant

correlations in favor of funding more prestigious (measured by US News Top 100 scores) (b= 17,856

p<0.01) and research institutions (measured by doctoral granting status) (b= 44,559 p<0.01). Similarly,

pre-trends show a significant, negative relationship between associate-granting colleges (b= -10,772

p<0.01), generally, and community colleges (b= -14,452, p<0.01), specifically, and FIPSE grant dollars.

Continuous measures of institutional capacity including endowment wealth (b= 0.00000450, p<0.01)

and instructional spending (b= 0.00399, p<0.01) also reflect this trend in favor of highly resourced

institutions in the pre-period (these coefficients express the relationship between one dollar of

endowment wealth or per-student instructional spending to one dollar of grant funding).

Figure 11 demonstrates that while the magnitude of relative benefits to higher prestige

institutions varies across time periods, it is consistently net-positive (i.e., above 0) and significantly

higher than the control program in both pre- and post-periods. In contrast, low-prestige associate-

granting institutions, illustrated in Figure 10, are at times at a net-negative (i.e., below 0) relative to their

higher-prestige counterparts and significantly lower than the control program in both pre- and post-

periods. Surprisingly, while resource allocation in favor of minoritized communities did gain traction

under this policy when compared to an entitlement program like SSS, the advantages awarded to

institutions with higher prestige and capacity as measured by doctoral-granting, endowment wealth,

and US News Top 100 status are not significantly changed by FITW. Similarly, the pre-trend showing a



negative relationship between associate-granting colleges (b= -10,914, p<0.1) or community colleges (b=

-19,473, p<0.05) and FIPSE grant receipt is exacerbated by FITW, which is also visible in Figure 9. The

pre-trends in favor of higher-capacity institutions are also exacerbated as measured by instructional

spending (b= 0.0095 p<0.1).

Causal estimates based on interaction of organization- and student-level measures. While the

predicted change in benefits to MSIs using multiple specifications bore out in the data, the predicted

change in the prestige and capacity of organizations did not. Given that non-prestigious, low-

endowment, and low-instructional spending colleges in U.S. postsecondary education serve a

disproportionately high share of low-income and minoritized students (see Table 9), this presents a

contradiction. To better understand this contradiction, we ran the MSI regression again isolating three

types of MSIs by interacting organizations’ MSI status with their degree-granting status (doctoral,

associate-granting, and other). As shown in Table 8, the pre-trend for MSIs of all types was negative and

statistically significant with the largest disadvantage prior to FITW for MSI doctoral-granting universities

(b= - 26,892, p<0.01), followed by MSI associate-granting colleges (b= -9,385, p<0.05, and all other MSIs

(b= -8,138, b<0.01). By disaggregating these organizations into smaller cells, we lose the statistical

power to see significant results in the triple interaction. However, the trends illustrated in Figure 12

demonstrate that while associate-granting MSIs and all other MSIs see either no or limited change,

respectively, MSI-doctoral granting universities increase sharply in the post-period above and beyond

the control program (b= 128,406). This closer analysis reveals the mechanism through which MSIs saw

their increased advantage: via doctoral granting organizational types. This finding and the general

persistence or increase in organizational prestige and capacity among FIPSE grantees in the post-period

creates a puzzle as the bulk of the causal effect in favor of MSIs comes from the organizational category

that, overall, serves the lowest proportion of poor and minoritized students (see Table 9).

Robustness and Limitations



The results presented in the previous section strongly suggest that FITW led to significant

increases in the delivery of grant funds to institutions serving minoritized students but did not

significantly affect the greater benefits awarded to institutions with higher levels of prestige and

capacity. The estimated increase was robust to controls for total enrollment, organizational sector and

degree-granting level, and region. In this section we present additional checks on the robustness of

these estimates and discussion of the overall limitations and assumptions of the study.

First, we conducted a placebo test using female enrollment as a factor unlikely to be affected by

the policy. We posit that replacing percent students of color enrolled with percent female enrolled rules

out the argument that FIPSE’s grantmaking profile was radically changing in ways unrelated to the intent

of the policy change in question. As expected, we do not find a significant effect of the policy on the

likelihood of grant receipt based on the percent of female students enrolled in an institution.

Next, we test whether the increase in grants to MSIs is due to an external increase in the

number of MSIs identified in the IPEDS system rather than to the policy change. For example, one can

imagine a scenario in which FIPSE has always served the same set of institutions, but it wasn’t until after

the policy change that these institutions began self-reporting as MSIs. To test this, we create a measure

of MSI status that is stable from 2010 through 2015 using the 2010 (pre-period) reported share of

minority students enrolled and re-estimate our main model. Using a stable, pre-period identifier of an

MSI institution does not alter the significance or direction of the results.

Finally, one could argue that these effects were not a result of the policy, but rather an

expression of a general trend toward funding diversity and inclusion programs. To test this, we conduct

the same set of regression analyses in a year in which no policy change occurred (2008). We do not find

a significant effect of the placebo policy change on the types of institutions receiving FIPSE awards

before and after 2008. We also conduct the same regression analyses using 2004 as a cut point, a year in

which the introduction of federal earmarking occurred without a change in frame, which we predict



would not have the same impact as FITW. These regressions produce only two statistically significant

results on different parameters of interest than demonstrated in the study of the FITW change. This

significant but entirely distinct effect provides further confidence that, in the current paper, we capture

the causal impact specifically of the FITW framing change.

One might also argue that the combination of framing and policy design changes indicated in

the archival analysis call into question the argument that framing played a significant role in this story.

Our analysis relies on the logical assumption that the design elements identified in our archival

analysis—increases to accountability and evidentiary requirements, increases grant size, and restricting

freedom in proposal designs—would not, on their own, have created a causal spike in service to poor

students and students of color. Additionally, our interview work on this case revealed that the role of

congress in influencing grantee selection was also diminished in the post period. While congress was

ostensibly bound by the same frame as FIPSE staff in the pre-period it is reasonable to ask if it was not

the frame, but this process change that led to the causal effect. In order to check this assumption, we

re-ran analyses dropping out grants from the pre-period that were congressionally directed. We found

that the same trends persist, albeit with fewer observations. We focus mainly on the model with all

observations for two reasons. First, it is the most complete representation of the activity of this federal

agency as it shifted from one framing to another and it recognizes the complexity of policy movement,

rarely confined to the most public aspects of the change. And second, the congressionally directed

grants also removed potential grantees from the competitive applicant pool, which would produce a

bias to results that drop these observations.

Our emphasis in this paper has been on the effect of frames on the selection of specific

organizations for grant funding to enable innovators to disrupt inequitable educational processes. While

we demonstrate that FIPSE funded quantifiably different institutions after the framing shift, we have not

analyzed the substantive content of the funded grant projects. Therefore, we cannot speak to the



possibility that perhaps every grant made to elite colleges in the pre-period was targeted specifically at

minoritized students, and every grant made to more diverse colleges in the post period perhaps was

not. This study focuses on the composition of organizations selected, a variable which we have argued is

material to the ultimate issue of addressing inequality in the field. In future work, we will extend our

analysis of the FITW framing change case study, drawing on already-collected qualitative descriptions of

each of FIPSE’s 4,400 granted programs. These data will allow us to code for the types of interventions

and target populations featured in each funded program. This extension will allow a more in-depth

analysis of how framing changes, like those enacted by FITW, affects grantmaking preferences.

Discussion

In today’s elite grantmaking circles, a few trends lend urgency to the empirical work undertaken

in this paper. First, many practitioners and scholars of higher education policy predict that as major

social problems persist, grantmakers’ efforts to catalyze change will play an increasingly influential role

in shaping intervention projects. Second, grantmakers are paying increasing attention to funding work

that upholds some vision of “equity,” just as FIPSE did in this case. However, there are no clear

boundaries around what “equity” is, who it is for, and how different conceptions of equity provide

varied affordances and constraints for change in a field like education. And third, the contested and

contingent nature of the role that categories like race and class will play in our collective, political future

suggests that the cognitive and cultural possibilities for combining grantmaking and concepts of “equity”

are far from settled. This paper leverages multiple forms of data to uncover causal impacts and to trace

how such changes hinged not only on a changing emphasis in favor of a minoritized target population,

but how this shift occurred in tandem with fundamental alterations to the design of grantmaking

programs. This finding exposes tensions intrinsic to any work intended to diminish inequalities.

By analyzing the intervenor rather than those on whom intervention is targeted, this study takes

a few steps toward unpacking how shifting emphases among elites guide what might be considered



legitimate political work in education. The mixed-methods findings demonstrate how a policy’s target

population gets coupled with assumptions about what that population does or does not lack, as well as

how closely these outcomes must be monitored. Philip, Bang & Jackson (2018) argue that paths

towards justice that interrupt institutionalized processes of inequality are simultaneously threatening to

dominant group privilege and as such, are less likely to be viewed as legitimate. From this place of

illegitimacy springs a tendency toward interest convergent reasoning (Philip & Azevedo, 2017;

Vossoughi & Vakil, 2018). We speculated that these stances introduce distinct limitations to the type of

work funded and thus advanced in a field.

While the FITW policy change could be interpreted at its face simply as a shift in favor of

investing in benefits to minoritized populations, our analysis of FIPSE’s archives demonstrates that there

are three additional axes on which the FITW change shifted FIPSE’s frame for action. From 1995 until the

administration revamped the program under FITW, FIPSE focused on general themes of improvement,

learning, and pedagogical experimentation to benefit “all students” in a system with a single, optional

priority (that did not carry structural weight) focused on access or diversity themes. The Obama-era

FITW program shifted the agency’s focus in favor of a class and race-conscious frame that mobilized the

needs of minoritized students specifically across all FIPSE priorities. As predicted by the literature, this

move to center minoritized populations in a policy was accompanied by a shift toward interest

convergent goals. Interest convergent reasoning emerged in this case in three ways as FIPSE’s espoused

target population shifted from broad (all students) to narrow (minoritized students). First, FIPSE’s

problem diagnoses shifted from the broad need to spur innovation to bring out the most promising

advancements in pedagogy, technology, and efficiency in higher education to a high-profile emphasis on

the role of higher education completion in international competitiveness and economic vitality that

would benefit all Americans. Specifically, the administration argued that this goal could not be met

without “closing the gap” of minoritized college completion. Indeed, “first in the world” was a reference



to a competition with other countries to hold the highest population of college degree holders as a

proxy for economic wellbeing. This finding fulfills critical race theory’s primary prediction that any

successful shift to favor minoritized populations will be accompanied by arguments about the benefits

dominant populations can expect from the policy change.

Second, rather than promoting the same solutions as in its pre-period, which broadly targeted

learning, affordability, access to engaging pedagogy, and completion, FIPSE limited its focus in

fulfillment of this interest convergent argument: solely promoting strategies expected to remediate

underperforming students to increase completion. While FIPSE had historically promoted the

advancement of student inquiry, civic knowledge, and other broad learning-based emphases in its open-

ended grant guidelines, the FITW frame shifted emphasis toward a prescriptive set of already defined,

deficit-oriented practices intended to remediate students. This extends the role of interest convergence

and fulfills policy design theory’s prediction that an emphasis on minoritized populations would be

followed by a decrease in the flexibility and creativity enjoyed by beneficiaries.

Third, whereas in the pre-period applicants were expected to pilot new, untested solutions as

part of the drive for innovation, in the post-period, FIPSE appealed to objectivity as a form of legitimacy

requiring rigorous evidence to substantiate proposals and a plan to causally demonstrate projects’

results. Indeed, FIPSE contracted an additional panel of evaluation experts to assure that any winning

proposal could pass muster in terms of its evidentiary backing. This emergent emphasis on rigorous

evaluation (e.g., experimental or quasi-experimental methods) was motivated by the need to build

evidence for practices that would affect market-based outcomes (e.g., college completion, employment

rates). This fulfills policy design theory’s prediction that an emphasis on minoritized populations would

be followed by an increase in the surveillance of and accountability required of beneficiaries.

The econometric analysis of the administrative dataset strongly suggests that the FITW policy

frame had its intended effect in terms of student-level target beneficiaries: at least ostensibly, more



students of color and poor students stood to benefit from this grant program than in FIPSE’s prior

years. While this may seem almost intuitive, it is critical to put this finding in context. This agency had

always been tasked with this same purpose—to address inequalities through educational improvement

for “underserved” students. And yet, the organizations predominantly serving these populations were at

a disadvantage according to all measures in their likelihood to receive FIPSE funding during FIPSE’s two

decades of operation prior to FITW. This speaks to the material effects of different cognitive and

cultural models of understanding inequality and improvement on policy implementation. Coupled with

results from our qualitative analyses, the quantitative results raise questions about the role of interest

convergence. Specifically, would the emphasis on minoritized populations under FITW have taken hold

if it had not been framed from the perspective of economic wellbeing for all?

However, the interpretation of the effect of this policy frame on beneficiaries is challenged

when turning to analyses of grant dollars awarded according to organization-level prestige and capacity

variables. From the perspective of service to the most underserved U.S. populations, this finding is non-

intuitive as the very institutions that, on average, serve the most minoritized students do not see

significant benefit (and even some negative effects) from the new policy frame. Coupled with the

positive findings regarding minoritized representation among award recipients, there is causal evidence

that this policy did not simply democratize the distribution of awards by delivering funds to the least

advantaged students at the institutions that primarily serve them (i.e., community colleges), but that

particular types of organizations serving minoritized students (who likely differ from minoritized

students at community colleges in relevant and measurable ways) received preference (i.e., research

universities). This upholds, in critical ways, policy design theory’s predictions that policies benefiting

minoritized populations will indeed redirect funds, but will also exhibit longer implementation chains

that involve more dominant populations (e.g., research staff at research universities), and will be the



target of higher surveillance in contrast to earlier programs that were subject to very little oversight and

were instead hailed as partners and innovators.

One interpretation of these findings—that more minoritized students were served under the

new frame, but not at the institutions primarily responsible for service to the most underserved

populations—is that only colleges with both this population and a moderate or high level of resource

and research capacity were considered legitimate. The changes in grantmaking patterns also align with

this explanation as FIPSE made fewer grants but in much larger amounts than in previous years to fund

this more intensive research and implementation chain. The FITW frame change did not result in an

unqualified change favoring the provision of funds and legitimacy to marginalized organizations that are

the most likely to disrupt the status quo in the field. In other words, FIPSE continued to preference an

organizational class whose success is largely determined by how it measures up against the most elite

universities in terms of rankings. These rankings are determined by institutionalized metrics that

preserve stratification and the status quo rather than stimulate change (Colyvas, 2012; Espeland &

Sauder, 2007). As such, this organizational class has little to no incentive for upending the field’s

hierarchy and stratifying practices. Instead of diminishing these sources of institutional persistence that

reproduce inequalities, this frame change shifted the mode of reproduction. Under the new condition, a

traditional source of legitimacy among elites in the academy—rigorous social scientific evaluation—

protects the institutional preference for more highly ranked and resourced colleges. This preference also

occurs as FIPSE ceases to provide funds for flexible and entrepreneurial “innovation” projects, instead

funding prescriptive strategies for student-focused remediation.

This contradiction surfaces the limitations that socially constructed categories may carry with

them into the policy design process. In previous eras, when FIPSE selected organizations that were

predominantly White and middle class, as well as prestigious with higher resource capacity, more liberal

conceptions of student learning, pedagogical experimentation, civic engagement, and global knowledge



predominated FIPSE’s archives and policies. These expansive values did not withstand the justice-

oriented political emphasis on minoritized populations. Instead, in this new era questions of learning,

pedagogy, and innovation were sidelined in favor of measurable outcomes expected to make

quantifiable contributions to the American economy.

Conclusion

The work of elites—whether in government or private philanthropy—to disrupt inequality

through the distribution of resources is often treated as if the agency’s or actors’ logics are not

themselves a variable in the success or failure of the field to adapt to more egalitarian purposes.

Researchers and government officials often strive to deeply interrogate the failure of individual

programs to produce measurable outcomes on the poor or on beneficiaries of color. However, the very

design and selection of such programs, a mere fraction and subset of what might have been proposed or

accepted under different elite framings, goes unexamined. In this analysis, we have scratched the

surface of how variation in an agency’s frames can dramatically affect grantmaking outcomes, while

preserving privilege and legitimacy at the organization level.

In this study, we examine the impacts of a grantmaking frame shift on the organizational type of

the recipient institutions—a proxy for the type of environment and the target population for which

contextualized innovations are developed. This case offers a powerful window into such processes given

that the agency under study was always ostensibly striving to disrupt higher education for the purpose

of offering more equitable outcomes to minoritized populations. However, the subtle shifts in the way

FIPSE framed its purpose ultimately have significant effects on who gets selected to innovate. Moreover,

a deep understanding of the impact of dominant cultural concerns on policy framing offers a lens

through which to interpret the pattern of results. When FIPSE adopted a racial and class justice frame

motivated by service to minoritized students, it did so using an interest convergent argument for



economic competitiveness. This new frame had a significant, positive effect on the proportion of

minoritized students served by selected grantees.

However, FIPSE coupled its renewed emphasis on racial and class inequality with a predictable

emphasis on prescriptive interventions and an unprecedented level of accountability. This frame

allowed outcomes to shift along one axis of the grantmaking profile—representation of minoritized

students. It also constrained this preference in part to institutions with the resources and prestige that

could support the program’s strict accountability demands. While this is not a normative argument that

such organizations should be excluded from improvement efforts, this case teaches us about how a

change in racial framing intended to diminish inequality can shift burdens and benefits such that

institutionalized inequality is still protected, but by different mechanisms. This result leaves modes of

reproduction that favor more elite and well-resourced organizations that are more likely to benefit from

the field’s current and inherently unequal institutional arrangements intact, thus reducing the

innovative potential that theory predicts could have come from funding creative work at marginalized

organizational types.



References

Apfelbaum, E. P., Norton, M. I., & Sommers, S. R. (2012). Racial color blindness: Emergence, practice,

and implications. Current Directions in Psychological Science, 21(3), 205–209.

Bastedo, Michael N., & Jaquette, O. (2011). Running in place: Low-income students and the dynamics of

higher education stratification. Educational Evaluation and Policy Analysis, 33(3), 318–339.

Bastedo, M.N., & Bowman, N. A. (2010). U.S. News & World Report college rankings: Modeling

institutional effects on organizational reputation. American Journal of Education, 116(2), 163–

183. https://doi.org/10.1086/649437

Béland, D. (2009). Ideas, institutions, and policy change. Journal of European Public Policy, 16(5), 701–

718. https://doi.org/10.1080/13501760902983382

Béland, D., & Cox, R. H. (2010). Ideas and politics in social science research. Oxford University Press.

Bell, D. A. (1980). Brown v. Board of Education and the interest-convergence dilemma. Harvard Law

Review, 518–533.

Benford, R. D., & Snow, D. A. (2000). Framing processes and social movements: An overview and

assessment. Annual Review of Sociology, 26, 611–639.

Bensimon, E. M., & Bishop, R. (2012). Introduction: Why “critical”? The need for new ways of knowing.

The Review of Higher Education, 36(1), 1–7. https://doi.org/10.1353/rhe.2012.0046

Berck, P., & Villas-Boas, S. B. (2016). A note on the triple difference in economic models. Applied

Economics Letters, 23(4), 239–242.

Berrey, E. (2011). Why diversity became orthodox in higher education, and how it changed the meaning

of race on campus. Critical Sociology, 37(5), 573–596.

https://doi.org/10.1177/0896920510380069

Berrey, E. (2015). The Enigma of Diversity. The University of Chicago Press. Retrieved from

http://www.press.uchicago.edu/ucp/books/book/chicago/E/bo19910067.html



Bonilla-Silva, E. (2013). Racism without racists: Color-blind racism and the persistence of racial inequality

in America (4 edition). Lanham: Rowman & Littlefield Publishers.

Brady, H. E., & Collier, D. (2004). Rethinking Social Inquiry: Diverse Tools, Shared Standards. Rowman &

Littlefield.

Brandtner, C., Bromley, P., & Tompkins-Stange, M. (2016). "Walk the line”: How institutional influences

constrain elites. In How Institutions Matter! (pp. 281–309). Emerald Group Publishing Limited.

Bromley, P., & Powell, W. W. (2012). From smoke and mirrors to walking the talk: Decoupling in the

contemporary world. Academy of Management Annals, 6(1), 483–530.

Brown, H. E. (2013). Racialized Conflict and Policy Spillover Effects: The Role of Race in the

Contemporary U.S. Welfare State. American Journal of Sociology, 119(2), 394–443.

https://doi.org/10.1086/674005

Clemens, E. S., & Cook, J. M. (1999). Politics and institutionalism: Explaining durability and change.

Annual Review of Sociology, 25(1), 441–466.

Coburn, C. E. (2006). Framing the problem of reading instruction: Using frame analysis to uncover the

microprocesses of policy implementation. American Educational Research Journal, 43(3), 343–

349. https://doi.org/10.3102/00028312043003343

Collier, D. (2011). Understanding process tracing. PS: Political Science & Politics, 44(4), 823–830.

https://doi.org/10.1017/S1049096511001429

Colyvas, J. A. (2012). Performance metrics as formal structures through the lens of social mechanisms:

When do they work and how do they influence? American Journal of Education, 118(2), 167–

197. https://doi.org/10.1086/663270

Colyvas, J. A., & Anderson, E. R. (under review). Institutionalization’s Quadrant and the micro-macro

dimension in organizational analysis.



Colyvas, J. A., & Jonsson, S. (2011). Ubiquity and legitimacy: Disentangling diffusion and

institutionalization. Sociological Theory, 29(1), 27–53. https://doi.org/10.1111/j.1467-

9558.2010.01386.x

Colyvas, J. A., & Powell, W. W. (2006). Roads to institutionalization: The remaking of boundaries

between public and private science. Research in Organizational Behavior, 27, 305–353.

Cox, R. D. (2016). Complicating conditions: Obstacles and interruptions to low-income students’ college

“choices.” Journal of Higher Education, 87(1), 1–26.

DiMaggio, P. (1997). Culture and cognition. Annual Review of Sociology, 23, 263-.

DiMaggio, P., & Anheier, H. K. (1990). The sociology of nonprofit organizations and sectors. Annual

Review of Sociology, 16(1), 137–159. https://doi.org/10.1146/annurev.so.16.080190.001033

DiMaggio, P., & Powell, W. W. (1983). The iron cage revisited: Collective rationality and institutional

isomorphism in organizational fields. American Sociological Review, 48(2), 147–160.

Dumas, M., & Anyon, J. (2006). Toward a critical approach to education policy implementation:

Implications for the (battle)field. In M. I. Honig (Ed.), New directions in education policy

implementation: Confronting complexity (pp. 149–168). Albany: State University of New York

Press.

Espeland, W. N., & Sauder, M. (2007). Rankings and Reactivity: How Public Measures Recreate Social

Worlds. American Journal of Sociology, 113(1), 1–40. https://doi.org/10.1086/517897

Espinoza, O. (2007). Solving the equity–equality conceptual dilemma: A new model for analysis of the

educational process. Educational Research, 49(4), 343–363.

https://doi.org/10.1080/00131880701717198

Feagin, J. R. (2006). Systemic racism. Routledge.



Gray, B., Purdy, J. M., & Ansari, S. (Shaz). (2014). From interactions to institutions: Microprocesses of

framing and mechanisms for the structuring of institutional fields. Academy of Management

Review, 40(1), 115–143. https://doi.org/10.5465/amr.2013.0299

Gutiérrez, K. D., & Jurow, A. S. (2016). Social design experiments: Toward equity by design. Journal of the

Learning Sciences, 25(4), 565–598.

Hand, V., Penuel, W. R., & Gutiérrez, K. D. (2013). (Re) framing educational possibility: Attending to

power and equity in shaping access to and within learning opportunities. Human Development,

55(5–6), 250–268.

Harper, S. R. (2012). Race without racism: How higher education researchers minimize racist

institutional norms. The Review of Higher Education, 36(1), 9–29.

https://doi.org/10.1353/rhe.2012.0047

Hartmann, D. (2015). Reflections on race, diversity, and the crossroads of multiculturalism. The

Sociological Quarterly, 56(4), 623–639. https://doi.org/10.1111/tsq.12096

Hild, M., & Voorhoeve, A. (2004). Equality of opportunity and opportunity dominance. Economics and

Philosophy, 20, 117–145.

Hirschman, D., Berrey, E., & Rose-Greenland, F. (2016). Dequantifying diversity: Affirmative action and

admissions at the University of Michigan. Theory and Society, 45(3), 265–301.

Jencks, C. (1988). Whom must we treat equally for educational opportunity to be equal? Ethics, 98(3),

518–533.

Jepperson, R. L. (1991). Institutions, institutional effects, and institutionalism. In W. W. Powell & P. J.

DiMaggio (Eds.), The new institutionalism in organizational analysis (pp. 143–163). Chicago, IL:

University of Chicago Press.

Kelley, J., & Evans, M. D. R. (1993). The legitimation of inequality: Occupational earnings in nine nations.

American Journal of Sociology, 99(1), 75–125.



Kelly, A. P., & James, K. (2015). Philanthropy goes to college. In F. M. Hess & J. R. Henig (Eds.), The New

Education Philanthropy: Politics, Policy, and Reform. Educational Innovations Series. Harvard

Education Press.

Kim, D. H., Colyvas, J. A., & Kim, A. K. (2016). Ideological call to arms: Analyzing institutional

contradictions in political party discourse on education and accountability policy, 1952–2012. In

How Institutions Matter! (pp. 329–391). Emerald Group Publishing Limited. Retrieved from

http://www.emeraldinsight.com/doi/pdf/10.1108/S0733-558X201600048A012

Leblebici, H., Salancik, G. R., Copay, A., & King, T. (1991). Institutional change and the transformation of

interorganizational fields: An organizational history of the US radio broadcasting industry.

Administrative Science Quarterly, 333–363.

Lee, C. D. (2009). Historical evolution of risk and equity: Interdisciplinary issues and critiques. Review of

Research in Education, 33(1), 63–100.

Lee, C. D., Spencer, M. B., & Harpalani, V. (2003). “Every shut eye ain’t sleep”: Studying how people live

culturally. Educational Researcher, 32(5), 6–13.

Lounsbury, M., & Crumley, E. T. (2007). New practice creation: An institutional perspective on

innovation. Organization Studies, 28(7), 993–1012.

Meyer, J. W. (1977). The effects of education as an institution. American Journal of Sociology, 83(1), 55–

77.

Meyer, J. W., & Jepperson, R. L. (2000). The ‘actors’ of modern society: The cultural construction of

social agency. Sociological Theory, 18(1), 100–120.

Meyer, J. W., & Rowan, B. (1977). Institutionalized organizations: Formal structure as myth and

ceremony. American Journal of Sociology, 83(2), 340–363.



Miksch, K. (2008). Institutional decision making and the politics of fear 30 years after Bakke. Realizing

Bakke’s Legacy: Affirmative Action, Equal Opportunity, and Access to Higher Education, 198–

218.

Miles, M. B., Huberman, A. M., & Saldana, J. (2013). Qualitative data analysis: A method sourcebook. CA,

US: Sage Publications.

Nasir, N. S., Rosebery, A. S., Warren, B., Lee, C. D., & Sawyer, R. K. (2006). Learning as a cultural process:

Achieving equity through diversity. The Cambridge Handbook of the Learning Sciences, 489–504.

Newman, F., & Cannon, W. (1971). Report on higher education. US Government Printing Office.

Norton, M. I., & Sommers, S. R. (2011). Whites see racism as a zero-sum game that they are now losing.

Perspectives on Psychological Science, 6(3), 215–218.

Orellana, M. F., & Bowman, P. (2003). Cultural diversity research on learning and development:

Conceptual, methodological, and strategic considerations. Educational Researcher, 32(5), 26–32.

Pedriana, N. (2006). From protective to equal Treatment: Legal framing processes and the

transformation of the women’s movement in the 1960s. American Journal of Sociology, 111(6),

1718–1761. https://doi.org/10.1086/499911

Philip, T. M., & Azevedo, F. S. (2017). Everyday science learning and equity: Mapping the contested

terrain. Science Education, 101(4), 526–532.

Philip, T. M., Bang, M., & Jackson, K. (2018). Articulating the “how,” the “for what,” the “for whom,” and

the “with whom” in concert: A call to broaden the benchmarks of our scholarship. Cognition and

Instruction, 36.

Phillips, D. J., & Zuckerman, E. W. (2001). Middle‐status conformity: Theoretical restatement and

empirical demonstration in two markets. American Journal of Sociology, 107(2), 379–429.

https://doi.org/10.1086/324072



Plaut, V. C., Thomas, K. M., & Goren, M. J. (2009). Is multiculturalism or color blindness better for

minorities? Psychological Science, 20(4), 444–446.

Powell, W. W., & Colyvas, J. A. (2008). Microfoundations of institutional theory. In R. Greenwood, C.

Oliver, R. Suddaby, & K. Sahlin-Andersson (Eds.), The SAGE Handbook of Organizational

Institutionalism (pp. 276–299). London: SAGE Publications, Ltd.

Purdie-Vaughns, V., Steele, C. M., Davies, P. G., Ditlmann, R., & Crosby, J. R. (2008). Social identity

contingencies: How diversity cues signal threat or safety for African Americans in mainstream

institutions. Journal of Personality and Social Psychology, 94(4), 615.

Quinn, R., Tompkins-Stange, M., & Meyerson, D. (2014). Beyond grantmaking: Philanthropic foundations

as agents of change and institutional entrepreneurs. Nonprofit and Voluntary Sector Quarterly,

43(6), 950–968. https://doi.org/10.1177/0899764013488836

Rattan, A., & Ambady, N. (2013). Diversity ideologies and intergroup relations: An examination of

colorblindness and multiculturalism. European Journal of Social Psychology, 43(1), 12–21.

https://doi.org/10.1002/ejsp.1892

Reckhow, S., & Snyder, J. W. (2014). The expanding role of philanthropy in education politics.

Educational Researcher, 43(4), 186–195.

Reckhow, S., & Tompkins-Stange, M. (2018). Financing the education policy discourse: Philanthropic

funders as entrepreneurs in policy networks. Interest Groups & Advocacy, 7(3), 258–288.

https://doi.org/10.1057/s41309-018-0043-3

Schneiberg, M. (2005). Combining new institutionalisms: Explaining institutional change in American

property insurance. In Sociological Forum (Vol. 20, pp. 93–137). Springer.

Schneiberg, M., & Lounsbury, M. (2008). Social movements and institutional analysis. The Handbook of

Organizational Institutionalism, 648, 670.



Schneider, A., & Ingram, H. (1993). Social construction of target populations: Implications for politics and

policy. American Political Science Review, 87(02), 334–347.

Schneider, A., & Sidney, M. (2009). What is next for policy design and social construction theory? Policy

Studies Journal, 37(1), 103–119.

Schuman, H., Steeh, C., Bobo, L., & Krysan, M. (1997). Racial attitudes in America: Trends and

interpretations. Harvard University Press.

Scott, R. (1995). Symbols and organizations: From Barnard to the institutionalists. Organization Theory:

From Chester Barnard to the Present and Beyond, 38–55.

Scott, W. R. (2013). Institutions and organizations: Ideas, interests, and identities (4th Edition). Thousand

Oaks, CA: Sage Publications, Inc.

Sears, D. O., & Henry, P. J. (2005). Over thirty years later: A contemporary look at symbolic racism.

Advances in Experimental Social Psychology, 37(95), 150.

Skrentny, J. D. (2006). Policy-elite perceptions and social movement success: Understanding variations in

group inclusion in affirmative action. American Journal of Sociology, 111(6), 1762–1815.

Snow, D. A., & Benford, R. D. (1988). Ideology, frame resonance, and participant mobilization.

International Social Movement Research, 1(1), 197–217.

Snow, D. A., Benford, R., McCammon, H., Hewitt, L., & Fitzgerald, S. (2014). The emergence,

development, and future of the framing perspective: 25+ years since “frame alignment.”

Mobilization: An International Quarterly, 19(1), 23–46.

Stephens, N. M., Fryberg, S. A., Markus, H. R., Johnson, C. S., & Covarrubias, R. (2012). Unseen

disadvantage: How American universities’ focus on independence undermines the academic

performance of first-generation college students. Journal of Personality and Social Psychology,

102(6).



Surel, Y. (2000). The role of cognitive and normative frames in policy-making. Journal of European Public

Policy, 7(4), 495–512. https://doi.org/10.1080/13501760050165334

Todd, A. R., Hanko, K., Galinsky, A. D., & Mussweiler, T. (2011). When focusing on differences leads to

similar perspectives. Psychological Science, 22(1), 134–141.

Tompkins-Stange, M. E. (2016). Policy Patrons: Philanthropy, Education Reform, and the Politics of

Influence. Educational Innovations Series. ERIC. Retrieved from

https://eric.ed.gov/?id=ED568742

Umbricht, M. R., Fernandez, F., & Ortagus, J. C. (2015). An examination of the (un)intended

consequences of performance funding in higher education. Educational Policy,

0895904815614398. https://doi.org/10.1177/0895904815614398

U.S. Department of Education. (2014, May 15). Press release: U.S. Department of education announces

$75 Million First in the World competition. Retrieved June 4, 2017, from

https://www.ed.gov/news/press-releases/us-department-education-announces-75-million-first-

world-competition

Vossoughi, S., & Vakil, S. (2018). Towards what ends? A critical analysis of militarism, equity and STEM

education. At War.

Warikoo, N. K., & Novais, J. de. (2015). Colour-blindness and diversity: Race frames and their

consequences for white undergraduates at elite US universities. Ethnic and Racial Studies, 38(6),

860–876. https://doi.org/10.1080/01419870.2014.964281

Witham, K., Malcom-Piqueux, L. E., Dowd, A. C., & Bensimon, E. M. (2015). America’s unmet promise:

The imperative for equity in higher education. Association of American Colleges and Universities.

Wooten, M. E. (2016). Institutional constraints on the pursuit of racial justice. In How Institutions

Matter! (Vol. 48B, pp. 261–280). Emerald Group Publishing Limited.

https://doi.org/10.1108/S0733-558X201600048B009



Yosso, T. J., Parker, L., Solorzano, D. G., & Lynn, M. (2004). From Jim Crow to affirmative action and back

again: A critical race discussion of racialized rationales and access to higher education. Review of

Research in Education, 28(1), 1–25.

Zucker, L. G. (1987). Institutional theories of organization. Annual Review of Sociology, 13(1), 443–464.



Tables

Table 1: FIPSE’s grantmaking history 1995-2015

Total FIPSE

Grants Awarded

Average Grant Size in

Dollars

Total Funds Distributed in

Dollars

1995 105 171,358 41,830,000 1996 71 179,655 12,760,000 1997 85 198,075 16,840,000 1998 99 210,701 20,860,000 1999 37 294,793 10,910,000 2000 129 285,906 194,800,000 2001 108 335,326 36,220,000 2002 85 352,326 29,950,000 2003 71 330,600 23,470,000 2004 368 371,815 136,800,000 2005 392 349,422 383,100,000 2006 68 393,199 26,740,000 2007 58 350,703 20,340,000 2008 350 290,730 101,800,000 2009 397 277,668 110,200,000 2010 381 360,129 398,600,000 2011 - - - 2012 - - - 2013 - - - 2014 27 2,771,000 74,820,000 2015 36 2,345,000 32,980,000

Note: While the agency continued to oversee its existing grants, FIPSE did not run its primary grant

programs in 2011-2013 as the Obama administration reworked the agency’s grantmaking framework.



Table 2: Independent variables

Institutional Characteristics

Population variables

Minority Serving Institution (50% or more students of color enrolled by IPEDS estimation), Average

Pell Grant per Student (as a proxy for low-income status), Historically Minority Serving Institution

Status (HBCU or Tribal college), Percent Black Students Enrolled, Percent Latinx Students Enrolled,

Percent Total Students of Color Enrolled

Source(s): Integrated Postsecondary Education Data System (IPEDS)

Mission & Capacity variables

Mission: Doctoral Granting Institution, Associate-Granting Institution, Public Two-Year Institution, US

News Top 100 Institution

Capacity variables: Per-student instructional spending; institutional endowment

Source(s): Carnegie Classifications; US News & World Reports; IPEDS

Other

FIPSE or SSS: Separate dummy variables for whether the institution is part of the FIPSE or SSS half of

the dataset in a given year

Source(s): U.S. Department of Education

Post: A dummy variable for whether the grant year in question occurred before or after the

implementation of FITW.

Table 3: Control Variables

Control Variables

Organizational sector fixed effects

Source(s): Integrated Postsecondary Education Data System (IPEDS)

Year fixed effects

Table 4: Dependent Variables

Grant Awards

FIPSE Grant Award (a dollar amount, or 0 if the institution did not receive a grant that year)

Source: U.S. Department of Education, FIPSE database (now defunct).

TRIO SSS Awards (a dollar amount, or 0 if the institution did not receive a grant that year)

Source: U.S. Department of Education



Table 5: Means and Standard Deviation for Selected Variables

Pre-FITW Post-FITW

All Colleges & Universities FIPSE Grantees SSS Grantees

All Colleges & Universities FIPSE Grantees SSS Grantees

mean sd mean sd mean sd mean sd mean sd mean sd

MSI 0.218 0.413 0.0889 0.285 0.176 0.381 0.335 0.472 0.302 0.463 0.283 0.451

HMSI 0.0167 0.128 0.0481 0.214 0.0784 0.269 0.0167 0.128 0.0794 0.272 0.0632 0.243 US News Top 100 School 0.0243 0.154 0.0777 0.268 0.0280 0.165 0.0240 0.153 0.111 0.317 0.0260 0.159 Doctoral granting institutions 0.0364 0.187 0.266 0.442 0.141 0.348 0.0404 0.197 0.270 0.447 0.159 0.366 Associate granting institutions 0.197 0.3p97 0.265 0.441 0.490 0.500 0.211 0.408 0.254 0.439 0.494 0.500 Community Colleges (Public Two-Years) 0.159 0.366 0.245 0.430 0.479 0.500 0.141 0.348 0.226 0.422 0.475 0.500 Pell Grant Scaled Per Student 2,274 3,230 1,174 836.4 1,464 931.0 2,511 2,832 1,524 1,070 1,587 766.3 Endowment Scaled Per Student

6.546e+07 5.684e+08

1.982e+08

8.560e+08 7.652e+07 3.014e+08 9.785e+07 7.893e+08

5.348e+08

1.851e+09

1.448e+08

5.666e+08

Instruction Scaled Per Student 13,427 80,506 10,348 23,125 6,567 11,130 15,132 87,118 13,474 25,712 7,958 13,589



Table 6: Difference-in-Difference-in-Difference Regressions with Year Fixed Effects: Causal Effects of FITW on Grant Awards to Institutions with High Proportions of Minoritized Students

Table 7: Difference-in-Difference-in-Difference Regression with Year and Sector Fixed Effects: Causal Effects of FITW on Grant Awards to Institutions Based on Prestige or Capacity

1: Minority Serving

Institutions (> 50%

minority)

2: Historically

Minority Serving

Institutions

3: High-Pell Serving

Institutions

4: Percent Black

Students Enrolled

5: Percent Students

of Color Enrolled

6: Pell Award Scaled

Per Student

FIPSE 2,464*** 1,718*** 2,584*** 1,531*** 1,557*** 2,066***

(564.3) (463.3) (521.4) (479.1) (484.4) (583.8)

FIPSE*Post-FITW -11,060*** -7,370*** -9,534*** -11,492*** -11,788*** -10,124***

(2,140) (2,007) (1,924) (2,000) (2,390) (2,448)

Characteristic 3,105*** 17,603*** 3,834*** 19.31 -43.95 0.318***

(468.1) (3,286) (507.8) (135.3) (51.58) (0.0396)

Char*Post -5,022*** 12,530** -1,350 -4,195** -1,654 -1.045***

(718.7) (5,039) (1,062) (1,892) (1,475) (0.0939)

Char*FIPSE (Pre-trend) -4,668*** -19,763*** -6,110*** -710.4** -436.8** -0.304***

(743.7) (4,092) (949.7) (313.6) (190.3) (0.0621)

Char*FIPSE*Post-FITW (Causal estimate) 14,942*** 11,656 12,003* 23,824*** 12,130** 1.205***

(5,113) (22,115) (6,830) (8,774) (5,284) (0.272)

Constant 16,979*** 17,350*** 17,051*** 17,610*** 17,416*** 17,642***

(3,753) (3,755) (3,754) (3,749) (3,750) (3,739)

Observations 205,060 205,060 205,060 205,060 205,060 205,060

R Squared 0.024 0.024 0.024 0.024 0.023 0.023

Time and Sector FE YES YES YES YES YES YES

Robust standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

Dependent Variable: Grant Award Amount

Student Population Characteristic

7: US News & World

Reports Top 100

Colleges &

Universities

8: Doctoral Granting

Universities

9: Associate-Degree

Granting Colleges

(public and private)

10: Community

Colleges (public two-

year colleges)

11: Endowment

Scaled Per Student

12: Instruction

Scaled Per Student

FIPSE 1,076** -207.0 3,539*** 3,943*** 1,869*** 1,337***

(462.6) (339.8) (515.5) (549.4) (435.9) (464.4)

FIPSE*Post-FITW -7,623*** -6,719*** -4,695** -5,400*** -8,591*** -7,333***

(1,999) (1,567) (1,982) (1,966) (2,058) (2,027)

Characteristic 2,280 18,625*** 4,252*** -5,376*** -6.80e-07** -0.0103***

(1,690) (2,074) (821.6) (1,745) -0.000000276 (0.00162)

Char*Post -409.7 28,035*** 12,606*** 24,586*** 1.44e-06** -0.00695**

(2,381) (3,242) (1,054) (1,608) (7.25e-07) (0.00292)

Char*FIPSE (Pre-trend) 17,856*** 44,559*** -10,772*** -14,452*** 4.50e-06** 0.00399***

(4,409) (7,671) (1,103) -1,346 (1.89e-06) (0.00122)

Char*FIPSE*Post-FITW (Causal estimate) 22,339 -18,696 -10,914* -19,473** 2.50e-06 0.00950*

(21,298) (31,771) (6,245) (9,221) (4.66e-06) (0.00576)

Constant 27,198*** 24,542*** 26,298*** 32,646*** 12,260*** 17,477***

(981.2) (852.5) (1,142) (1,696) (3,644) (3,755)

Observations 205,060 205,060 205,060 186,987 188,983 204,988

R Squared 0.017 0.027 0.017 0.019 0.021 0.023

Time and Sector FE YES YES YES YES YES YES


*** p<0.01, ** p<0.05, * p<0.1


Organizational Characteristic



Table 8: Difference-in-Difference-in-Difference Regression with Year and Sector Fixed Effects: Causal Effects of FITW on Grant Awards to Institutions Based on Interaction of MSI and Organization Type

13: Minority-

Serving Doctoral

Universities

14: Minority-

Serving Associate

Granting Colleges

15: Other

Minority Serving

Institutions

FIPSE 25,095*** -7,515*** 1,825***

(3,388) (1,047) (627.9)

FIPSE*Post-FITW -28,452*** -20,675** -8,432***

(7,326) (8,824) (2,012)

Characteristic 1,992 8,105*** 8,840***

(2,528) (2,595) (1,346)

Char*Post 10,494* -1,220 2,395

(5,943) (4,034) (2,231)

Char*FIPSE (Pre-trend) -26,892*** -9,385** -8,138***

(4,571) (4,076) (1,721)

Char*FIPSE*Post-FITW (Causal estimate) 128,406 -796.0 2,968

(82,691) (12,199) (7,432)

Constant 64,376*** 24,132*** 25,501***

(5,072) (1,148) (7,758)

Observations 24,448 35,722 60,997

R Squared 0.024 0.011 0.025

Time and Sector FE YES YES YES


*** p<0.01, ** p<0.05, * p<0.1


Interacted Characteristic



Table 9: Proportions of Underrepresented Minority (URM) and Total Enrollment in 2005, 2010, and 2015 by Institutional Type

2005 2010 2015

Percent URM

Served within Type

Proportion of URM Students

Enrolled in College Served

by this Type

Proportion of Total Students


by this Type

Percent URM

Served within Type



by this Type



by this Type

Percent URM

Served within Type



by this Type



by this Type

Doctoral Granting Universities 17.50% 14.10% 22.40% 24.20% 15.10% 21.60% 28.10% 19.80% 25.90%

Masters Granting Colleges 24.70% 15.20% 17.10% 29.30% 14.60% 17.30% 32.30% 16.50% 18.80%

US News & World Report’s Top 100 Colleges and Universities 13.10% 2.33% 4.94% 18.20% 2.54% 4.82% 20.10% 2.48% 4.55%

Associate Granting Colleges (public and private) 30.90% 41.50% 37.40% 37.10% 43.80% 40.70% 41.90% 44.20% 38.70%

Community Colleges (Public Two-Year Colleges) 29.70% 38.80% 36.50% 35.70% 38.60% 37.30% 41.00% 38.20% 34.30%

High Endowment Institutions 20.30% 23.50% 32.30% 25.20% 20.10% 27.50% 28.20% 22.50% 29.30%

Low Endowment Institutions 31.50% 24.40% 21.60% 38.20% 39.80% 36.00% 43.10% 39.10% 33.30% High Instructional Spending Institutions 18.80% 11.60% 17.20% 21.80% 14.90% 23.60% 24.20% 14.30% 21.80% Low Instructional Spending Institutions 39.30% 27.40% 19.40% 56.30% 20.80% 12.70% 52.00% 27.80% 19.60%



Figures

Figure 1: FIPSE’s Frame and Policy Design 1995 – 2010 (Pre-FITW)

Figure 2: FIPSE’s Frame and Policy Design 2013-2015 (post-FITW)

Figure 3: 1995 FIPSE Comprehensive Program Grant Guidelines, page 1

Colorblind/Multicultural Frame Target Population (beneficiary)

Broad: Multiple populations or undefined populations. No priority given to serving any one population.

Diagnostic Emphasis (the problem)

Innovation-driven emphasis on the need to move out of existing models relevant to many higher education issues

Prognostic Emphasis (the solution)

Multiple: Student learning assessment, pedagogical change, technological advancement, new credit assessment structures, access and completion, efficiency and funding structures, global education, STEM

Policy Design

Unrestrictive Design Standards Priorities describe a broad problem and welcome promising solutions, as well as solutions to problems not listed

Low accountability, Surveillance and Evidentiary Standards Applicants are not expected to provide existing evidence that their proposal will work (because it is innovative and potentially untested). They are expected to submit a brief evaluation plan not held to experimental or quasi-experimental standards.

Broad Funding Distribution Plan The agency plans to make many (approximately between 80 and 300) grants of moderate size.

Policy Design

Restrictive Design Standards Application priorities each describe a single, categorical intervention type. Solutions to unlisted problems are not allowed.

High Accountability, Surveillance and Evidentiary Standards Applicants are expected to provide robust, existing evidence from published literature or their own randomized control (RCT) trials that their proposal will work. They are required to submit a rigorous evaluation plan using either an RCT or quasi-experimental model for evaluation. Narrow Funding Distribution Plan The agency plans to make only a few (approximately between 30 and 70) grants of large size.

Racial & Class Justice Frame Target Population (beneficiary)

Narrow: Specific marginalized, minority populations are emphasized frequently and are given funding preference

Diagnostic Emphasis (the problem)

A decline in national standing and economic competitiveness due to lagging college completion which is a detriment of all Americans, and which requires more minorities to graduate college

Prognostic Emphasis (the solution)

Singular: Highly specific tactics targeting student-level remediation





If you embark upon a funded grant project starting in the fall of 2006, keep in mind that the project may not reach full maturity and achieve significant impact nationally for six to eight years. Changes such as the dramatic rise of information technology, the increasing diversity of postsecondary learners, the renewed demand for accountability, or the rise of competition among postsecondary providers are powerful enough to shape the immediate future of postsecondary education. We urge you to anticipate these dynamic forces of change and to develop bold new project ideas. These projects should aim to reshape the postsecondary education system so that its practices, values, and results are not simply the product of evolutionary drift. FIPSE urges the field to develop education reform proposals in the context of a changing world.

Figure 6: 2015 FIPSE FITW Grant Guidelines, page 27,036 Federal Register, Vol. 80, No. 90




Figure 9: The Effect of the First in the World Policy Frame Change on the Grant Benefits Awarded Based

on Student Population Measures

Note: “High-Pell Serving" is a proxy for colleges and universities

that serve a high-proportion of low-income students (who are

thus eligible for the need-based federal Pell grant).

Minority-Serving Institutions

High-Pell Serving Institutions (top quintile)

Gra

nt

Do

llars

Aw

ard

ed t

o H

igh

-Pel

l Ser

vin

g

Rel

ativ

e t

o O

ther

Co

llege

s

Gra

nt

Do

llars

to

Min

ori

ty-S

ervi

ng

Rel

ativ

e

to W

hit

e-S

ervi

ng

Co

llege

s



Figure 10: The Effect of the First in the World Policy Frame Change on the Grant Benefits Awarded to

Low-Prestige/Low-Capacity Institutions

Low Endowment Institutions (bottom quintile)

Associate Degree Granting Colleges

Community Colleges (public, two-years) Low Per-Student Instructional Spending Institutions

Gra

nt

Do

llars

to

Lo

w-E

nd

ow

me

nt

Rel

ativ

e

to O

the

r C

olle

ges

Gra

nt

Do

llars

to

Ass

oci

ate

Deg

ree

Gra

nti

ng

Rel

ativ

e t

o O

ther

Co

llege

s

Gra

nt

Do

llars

to

Co

mm

un

ity

Co

llege

s

Rel

ativ

e t

o O

ther

Co

llege

s

Gra

nt

Do

llars

to

Lo

w In

st. S

pe

nd

ing

Co

llege

s R

elat

ive

to O

ther

Co

llege

s



Figure 11: The Effect of the First in the World Policy Frame Change on the Grant Benefits Awarded to

High-Prestige/High-Capacity Institutions

High Endowment Institutions (top quintile)

U.S. News & World Reports’ Top 100 Institutions

Doctoral Granting Research Universities

High Per-Student Instructional Spending Institutions

Gra

nt

Do

llars

to

Hig

h E

nd

ow

men

t R

elat

ive

to O

the

r C

olle

ges

Gra

nt

Do

llars

to

Do

cto

ral G

ran

tin

g R

elat

ive

to O

the

r C

olle

ges

Gra

nt

Do

llars

to

To

p 1

00 R

elat

ive

to O

the

r

Co

llege

s

Gra

nt

Do

llars

to

Hig

h In

st. S

pen

din

g

Co

llege

s R

elat

ive

to O

ther

Co

llege

s



Figure 12: The Effect of the First in the World Policy Frame Change on Minority Serving Institutions

Disaggregated by Doctoral Universities, Associate Granting Colleges, and all Other MSI Type

Minority-Serving Associate Granting Colleges Minority-Serving Doctoral Universities

All Other Minority-Serving Types

Gra

nt

Do

llars

to

MSI

Rel

ativ

e to

No

n-M

SI

Inst

itu

tio

ns

Gra

nt

Do

llars

to

MSI

Rel

ativ

e to

No

n-M

SI

Inst

itu

tio

ns

Gra

nt

Do

llars

to

MSI

Rel

ativ

e to

No

n-M

SI

Inst

itu

tio

ns

association for education finance and policy - disrupting or … · 2019-03-25 · disrupting or...

Documents