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Record W2890283937 · doi:10.3917/spub.184.0013

Universalisme proportionné : vers une « égalité réelle » de la prévention en France ?

2018· article· fr· W2890283937 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSanté Publique · 2018
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Although their design may feature a considerable amount of universalism, prevention strategies often produce results that are socially and/or spatially differentiated. This differentiation process can induce social or territorial gradients of access to and/or effectiveness of prevention and, in turn, worsen health inequalities. This process also accentuates the gap between the principles of certain public policies and their practical implementation, raising the question of the real benefit of these policies for beneficiaries. Although Sir Marmot considers proportionate universalism to be a strategy to tackle health inequalities, the practical modalities of implementation of this principle have been rarely described in the literature until very recently. This pragmatic paper therefore presents a causal analysis of differentiation processes, underlines the need for self-reflexive prevention strategies, and investigates practical implications of proportionate universalism.

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.

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.745
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.026
GPT teacher head0.423
Teacher spread0.397 · 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