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Record W4244698721 · doi:10.22215/etd/2008-06510

From the Medical Research Council to the Canadian Institutes of Health Research: understanding transformational institutional change /Joan Murphy.

2008· dissertation· en· W4244698721 on OpenAlexfundaboutno aff
Joan Murphy

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchHealth CanadaMinistère de la Défense NationaleNatural Sciences and Engineering Research Council of CanadaPromotion and Mutual Aid Corporation for Private Schools of JapanMedical Research Council CanadaAgency for Health Care Policy and ResearchCanadian Medical AssociationNational Cancer InstituteSocial Sciences and Humanities Research Council of CanadaRoyal College of Physicians and Surgeons of CanadaUniversity of TorontoNational Institutes of HealthU.S. Department of Health and Human ServicesQueen's UniversityMedical Research CouncilHoward Hughes Medical InstituteAlberta Heritage Foundation for Medical ResearchFondation pour la Recherche MédicaleMcGill UniversityHeart and Stroke Foundation of Canada
KeywordsTransformational leadershipPolitical scienceLibrary scienceSociologyHumanitiesArtPublic relationsComputer science

Abstract

fetched live from OpenAlex

conserver, transmettre au public par telecommunication ou par I'lnternet, prefer, distribuer et vendre des theses partout dans le monde, a des fins commerciales ou autres, sur support microforme, papier, electronique et/ou autres formats.

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)0.021
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.604

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.010
Science and technology studies0.0150.019
Scholarly communication0.0110.011
Open science0.0030.006
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0300.002

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 head0.826
GPT teacher head0.529
Teacher spread0.297 · 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

Citations0
Published2008
Admission routes2
Has abstractyes

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