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The Politics of Inclusive Development

2014· book· en· W1860978058 on OpenAlexfundno aff
Kunal Sen, Badru Bukenya

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
FundersErasmus Universiteit RotterdamUniversity of ManchesterInternational Development Research CentrePrinceton UniversityTemple UniversityYale UniversityEconomic and Social Research CouncilWorld Health OrganizationWorld Bank Group
KeywordsPoliticsOriginalityCorporate governanceEmpowermentScope (computer science)Political scienceSociologyEngineering ethicsEnvironmental ethicsSocial scienceManagementEngineeringLawEconomicsComputer science

Abstract

fetched live from OpenAlex

Abstract It is now widely accepted that politics plays a significant role in shaping the possibilities for inclusive development. However, the specific ways in which this happens across different types and forms of development, and in different contexts, remains poorly understood. This collection provides the state of the art review regarding what is currently known about the politics of inclusive development. Leading academics offer systematic reviews of how politics shapes development across multiple dimensions, including through growth, natural resource governance, poverty reduction, service delivery, social protection, justice systems, the empowerment of marginalized groups, and the role of both traditional and non-traditional donors. The book not only provides a comprehensive update but also a groundbreaking range of new directions for thinking and acting around these issues. The book’s originality thus derives not only from the wide scope of its case-study material, but also from the new conceptual approaches it offers for thinking about the politics of inclusive development, and the innovative and practical suggestions for donors, policymakers, and practitioners that flow from this.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.012
Scholarly communication0.0100.006
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0090.002

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 head0.012
GPT teacher head0.291
Teacher spread0.279 · 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 designTheoretical or conceptual
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".

Quick stats

Citations104
Published2014
Admission routes1
Has abstractyes

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