Ending the Transformation before the Goal is Fulfilled: The Case of Head Start

• Author: Ilana Shpaizman
• DOI: http://doi.org/10.1177/00953997221147225
• Published date: 01 March 2023
• Date: 01 March 2023
• Subject Matter: Articles

https://doi.org/10.1177/00953997221147225

Administration & Society

2023, Vol. 55(3) 381 –404

© The Author(s) 2023

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DOI: 10.1177/00953997221147225

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Article

Ending the

Transformation before

the Goal is Fulfilled:

The Case of Head Start

Ilana Shpaizman1

Abstract

To make a comprehensive policy change, actors often turn to the

gradual path where they introduce small-scale changes hoping that their

accumulation will meet their goal over time. Nonetheless, they often stop

the transformative process before meeting their original goal. This paper

argues that this can be explained by policy learning. When actors learn from

reliable information that the accumulation of the small-scale changes does

not meet their expectations, they stop the transformative process. At the

same time, the policy is not illuminated due to feedback effects and beliefs

by the majority of actors that the small-scale changes are beneficial.

Keywords

child care, policy learning, gradual transformative change

Introduction

Actors wishing to promote a significant policy change often face many insti-

tutional, political, and cognitive obstacles (Baumgartner & Jones, 2010). One

way to bypass these obstacles is to gradually meet their goal by introducing

small-scale changes that, over time, lead to a shift from the status quo. This

1Bar Ilan University, Ramat Gan, Israel

Corresponding Author:

Ilana Shpaizman, Department of Political Studies, Bar Ilan University, Ramat Gan 5290002, Israel.

Email: Ilana.shpaizman@biu.ac.il

1147225AAS0010.1177/00953997221147225Administration & SocietyShpaizman

research-article2022

382 Administration & Society 55(3)

strategy has been used in many policy fields in the last 60 years (Streeck &

Thelen, 2005; van der Heijden & Kuhlmann, 2017). Some prominent exam-

ples are the Republican party’s efforts to replace Medicare by gradually intro-

ducing private insurance plans and blocking efforts to update the existing

structures (Hacker, 2004) or the gradual changes made in Social Security

(Béland, 2007).

Nonetheless, when closely examining the various examples, one finds that

often, while actors were able to shift the status quo, they still had not met

their initial goal after many years. For instance, both Medicare and Social

Security are still active. Although some of the transformative processes might

still be in progress, others stagnated and became adaptive; no new initiatives

have been introduced, no expansion of the existing instruments or strategies

has taken place, and most of the attention has turned to adjust existing struc-

tures. All that even though actors did not change their original goals and were

not forced to stop the transformation. This raises the question of why actors

stop the transformative process before meeting their original goal.

So far, we do not have a sufficient answer to this question. For the most

part, existing research on gradual transformative policy change focuses on

the shift from the status quo that has taken place and its causes. However, it

does not examine to what extent this shift has fulfilled actors’ initial goals.

This is important because focusing only on the successes of the gradual trans-

formative change can lead to a distorted valuation of this change strategy,

seeing it as more successful than it is.

The few existing works that look beyond the shift from the status quo have

pointed to the role a powerful opposition can have on the stagnation of the

transformative process (Mandelkern & Koreh, 2018) or to instances when

negative feedback causes actors to reverse the transformation (Shpaizman,

2017). This paper aims to shed light on another mechanism that could operate

in dynamics unfolding over a long period—policy learning.

Learning occurs when there are policy anomalies, discrepancies between

the expectations and the outcomes (Hall, 1993; May, 1992; Sabatier &

Jenkins-Smith, 1993). In a gradual transformative change, actors have expec-

tations about the policy’s immediate outcome and the accumulated effect, the

estimated effect of the accumulation of small-scale changes over time. The

nature of the gradual process makes it likely to experience policy anomalies

regarding the accumulated effect. Since the information processing of actors

is not proportional (Baumgartner & Jones, 2015), actors will pay attention to

the anomalies only when the level of conflict is moderate and when reliable

information accumulates (Jenkins-Smith et al., 2014). Then, policy learning

will take place; actors will update their beliefs about the expected accumu-

lated effect of the instrument. In other words, they will no longer believe that