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Record W4405894699 · doi:10.20899/jpna.nsb51y51

French-Language Public Administration Research on Social Equity: A Systematic Literature Review

2024· article· en· W4405894699 on OpenAlexaff
Gino Biaou, Étienne Charbonneau

Bibliographic record

VenueJournal of Public and Nonprofit Affairs · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsÉcole Nationale d'Administration Publique
Fundersnot available
KeywordsEquity (law)ScholarshipSociologyPublic relationsPolitical sciencePositive economicsEconomicsLaw

Abstract

fetched live from OpenAlex

Despite the availability of freely accessible translation tools, research conducted in languages other than English is often overlooked. Findings from foreign contexts are lost, undermining the boundary conditions of theories. This systematic literature review takes stock of methods, theories, and practical recommendations developed in French-language social equity research. Overall, the results suggest that French-language social equity research offers relevant but not in-depth practical recommendations, encompasses a small proportion of papers referring to theories, and is more qualitative method-oriented than quantitative. Our results complement previous findings suggesting the dominance of the quantitative approach to social equity research by bringing to light many qualitative studies. Crucially, unlike English-language social equity research, this study suggests that French-language social equity research rarely focuses on race and ethnicity. Inter-organizational equity, along with regional, intergenerational, and gender equity are frequent loci. The finding of this study bridges a heeded segment of Public Administration scholarship, fostering knowledge sharing across languages and scholarly communities.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.040
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.911
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0400.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0030.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.409
GPT teacher head0.575
Teacher spread0.166 · 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 teacher head, not a consensus.

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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