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Record W2790619641 · doi:10.22215/etd/2016-11722

Policy Adoption in International Organizations: The Case of the Social Protection Floor Initiative

2016· dissertation· en· W2790619641 on OpenAlexaff
Yelda Gulderen

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsCarleton University
FundersUnited Nations Development ProgrammeUNICEF
KeywordsSupporterPolitical scienceScope (computer science)Public administrationBusinessEconomic growthEconomics

Abstract

fetched live from OpenAlex

This dissertation project examines the Social Protection Floor Initiative (SPF-I), a global social policy initiative that brought together various international organizations which have traditionally had divergent social policy approaches.Since the launch of the SPF-I in 2009, most of the major international organizations in the development field became part of the Initiative and engaged in the Social Protection Floor (SPF) policy at varying levels.This project focuses on six international organizations, namely the United Nations Children's Fund (UNICEF), the United Nations Development Programme (UNDP), the World Health Organization (WHO), the Organization for Economic Cooperation and Development (OECD), the World Bank, and the International Monetary Fund (IMF).The overarching research question is, "what explains the extent of, and the variation in, the international organizations' adoption of a given policy (in this case, the SPF)?"In order to explain the extent of policy adoption in international organizations, a policy adoption matrix has been developed.This matrix helps to identify each international organization as a policy leader, policy follower, or policy supporter based on the following parameters: the speed and the timing of policy adoption, the level of commitment, the breadth of organizational buy-in, and the scope of policy adoption.While the UNICEF, the UNDP, and the WHO are identified as policy leaders, the OECD is identified as a policy follower, and the World Bank and the IMF are identified as policy supporters.iii Next, this study explains why these international organizations are policy leaders, followers, or supporters.The analysis of policy adoption in the six international organizations reveals that: (i) the presence of policy entrepreneurs within relevant networks and the policy's good fit in the organizations' outlook explain why the UNICEF, the UNDP, and the WHO are policy leaders, (ii) the role of member states and the policy's poor fit in the organization's outlook explain the OECD's role as a policy follower, and (iii) the external pressures and the policy's poor fit in the organizations' outlook explain why the World Bank and the IMF are policy supporters.This analysis concludes with an analytical framework towards a theory of policy adoption in international organizations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0330.033
Scholarly communication0.0200.010
Open science0.0020.017
Research integrity0.0090.013
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.377
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2016
Admission routes1
Has abstractyes

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