MétaCan
Menu
Back to cohort
Record W2520597054 · doi:10.4000/ethiquepublique.2153

Les enjeux éthiques associés à la transformation des systèmes de soins

2003· article· fr· W2520597054 on OpenAlexvenueaboutno aff
André‐Pierre Contandriopoulos

Bibliographic record

VenueÉthique Publique · 2003
Typearticle
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Plusieurs facteurs convergents expliquent les situations de crise qui affligent les systèmes de santé de nombreux pays et auxquels le Canada n’échappe pas. La crise actuelle soulève non seulement des questions d’ordre opérationnel et économique, mais suscite également des questions fondamentalement éthiques. En effet, une analyse des diverses conceptions des systèmes de santé révèle qu’elles comportent des orientations idéologiques reposant sur un ensemble de valeurs cardinales au sujet desquelles la société québécoise devra débattre. Pour mieux cerner les enjeux en cause, on doit également comprendre que la régulation du système de santé reflète le résultat de la concurrence et de la coopération entre plusieurs logiques distinctes. Dans la mesure où l’on doit reconnaître les causes et l’ampleur de la crise actuelle, nous devons renoncer au statu quo, qui s’avère d’autant plus difficile que la force d’inertie face au changement provient en partie du fait que le système de santé canadien nous apparaît comme une institution légitime fondée sur des valeurs auxquelles nous tenons. Face à deux options possibles, la privatisation ou la réforme, nous devons relever le défi plus complexe et difficile de la réforme, ce qui implique en retour une réflexion en profondeur concernant les stratégies de changement.

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)0.006
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.029
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0060.026
Scholarly communication0.0080.005
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.061
GPT teacher head0.395
Teacher spread0.334 · 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".

Quick stats

Citations9
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueÉthique PubliqueSame topicHealth, Medicine and SocietyFrench-language works237,207