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Record W2569818566 · doi:10.9778/cmajo.20160064

Canadian Institutes of Health Research funding of prison health research: a descriptive study

2017· article· en· W2569818566 on OpenAlexafffundvenueabout
Fiona G. Kouyoumdjian, Kathryn E. McIsaac, Jessica Foran, Flora I. Matheson

Bibliographic record

VenueCMAJ Open · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsMcMaster UniversityNova Scotia Health Authority
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsPrisonGovernment (linguistics)Political scienceFunding AgencyAgency (philosophy)Descriptive researchGrant fundingHealth carePublic administrationPublic relationsSociologySocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Health research provides a means to define health status and to identify ways to improve health. Our objective was to define the proportion of grants and funding from the Government of Canada's health research investment agency, the Canadian Institutes of Health Research (CIHR), that was awarded for prison health research, and to describe the characteristics of funded grants. METHODS: In this descriptive study, we defined prison health research as research on the health and health care of people in prisons and at the time of their release. We searched the CIHR Funding Decisions Database by subject and by investigator name for funded grants for prison health research in Canada in all competitions between 2010 and 2014. We calculated the proportion of grants and funding awarded for prison health research, and described the characteristics of funded grants. RESULTS: During the 5-year study period, 21 grants were awarded that included a focus on prison health research, for a total of $2 289 948. Six of these grants were operating grants and 6 supported graduate or fellowship training. In total, 0.13% of all grants and 0.05% of all funding was for prison health research. INTERPRETATION: A relatively small proportion of CIHR grants and funding were awarded for prison health research between 2010 and 2014. If prison health is a priority for Canada, strategic initiatives that include funding opportunities could be developed to support prison health research in Canada.

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)0.024
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.709
GPT teacher head0.589
Teacher spread0.120 · 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 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

Citations6
Published2017
Admission routes4
Has abstractyes

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