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Record W2322332679 · doi:10.3138/cjpe.30.3.07

Considering the Social Determinants of Equity in International Development Evaluation Guidance Documents

2016· article· en· W2322332679 on OpenAlexvenueno aff
Kelly Robertson

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsEquity (law)BusinessSocial equalityPublic economicsPublic relationsPolitical scienceAccountingEconomics

Abstract

fetched live from OpenAlex

Abstract: Several international development organizations have published equity-focused evaluation guidance documents to promote and meet an increased demand for equity-focused evaluation practice. Evaluating progress toward equity necessitates focusing on changes in the social determinants of equity (i.e., barriers and enabling factors). Thus, the purpose of this study is to describe how and the extent to which international development organizations recommend addressing the social determinants of equity in evaluation practice guidance documents. Implications for evaluation quality, cultural responsiveness, and the decolonization of evaluation are discussed and a summary of practical examples and guidance is presented.

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)0.313
metaresearch head score (Gemma)0.427
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.313
Threshold uncertainty score0.847

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3130.427
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.006
Science and technology studies0.0080.012
Scholarly communication0.0230.013
Open science0.0030.014
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0050.000

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 head0.519
GPT teacher head0.604
Teacher spread0.085 · 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.

Study designQualitative
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

Citations2
Published2016
Admission routes1
Has abstractyes

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