MétaCan
Menu
Back to cohort
Record W7018905832

Explaining knowledge use among clients of the Program Training & Consultation Centre

2001· dissertation· en· W7018905832 on OpenAlexaboutno aff

Bibliographic record

VenueTSpace (University of Toronto) · 2001
Typedissertation
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsnot available
Fundersnot available
KeywordsTraining (meteorology)Knowledge levelAgency (philosophy)Knowledge acquisitionProgram evaluationContext (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

The central question this research answered was What factors account for variation in knowledge use following receipt of service from the Ontario Tobacco Strategy 's Program Training and ConruIiation Centre (PTCC)?Its intent was to extend understanding of theoretical constmcts related to knowledge utilisation in the context of health promotion.A review indicated that relaiively little systematic effort has examined how health promoters use research and that existing research had used a limited set of variables to explain health promotion research use.A framework fiom education (Cousins & Leithwood, 1993) provided an opportunity to test an expanded range of variables in public health.The h e w o r k consists of variable domains related to (a) the Source and Information, (b) the Setting for Improvement and (c) Interactive Processes.Study 1 consisted of a stmctured telephone interview of 18 1 heaith unit staff (86% response rate) listed as PTCC clients in the past year.The survey sought respondent perceptions about the intervention using quantitative measures of variables derived fkom the SOURCE AND INFORMATION domain.Principal components anaiysis identified conceptual (CKU e-g., learning) and instrumental (KU e.g., decision-making) uses of knowledge.Hierarchical regression analyses indicated two factors (intervention intensity How can 1 repay the significant withdrawals I've made on the social capital of these various communities?Sticky buns for all. . ....

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.090
GPT teacher head0.387
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 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

Citations0
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueTSpace (University of Toronto)Same topicInnovative Education and Learning PracticesFrench-language works237,207