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Record W2409107290 · doi:10.1186/s13034-016-0103-x

Building research capacity in child welfare in Canada

2016· article· en· W2409107290 on OpenAlexafffundabout
Nico Trocmé, Catherine F. Roy, Thomas J. Esposito

Bibliographic record

VenueChild and Adolescent Psychiatry and Mental Health · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversité de MontréalMcGill University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAgency (philosophy)WelfareCapacity buildingPublic relationsService (business)Political scienceBusinessEconomic growthSociologyEconomicsMarketingSocial scienceLaw

Abstract

fetched live from OpenAlex

There is a surprising dearth of information about the services provided to the children and families being reported to Canadian child welfare authorities, little research on the efficacy of child welfare services in Canada, and limited evidence of new policies and programs designed to address these changes. This paper reports on a research capacity building initiative designed to address some of these issues. By fostering mutual co-operation and sharing of intellectual leadership, the Building Research Capacity initiative allows partners to innovate, build institutional capacity and mobilize research knowledge in accessible ways. The model rests on the assumption that by placing the university's research infrastructure at the service of community agencies, robust research partnerships are developed, access to agency-based research is significantly enhanced and community agencies make better use of research findings which all equate in greater research utilization and research capacity building.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.282
GPT teacher head0.549
Teacher spread0.267 · 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 designObservational
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

Citations27
Published2016
Admission routes3
Has abstractyes

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