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Record W47101223 · doi:10.3138/cjpe.0015.003

Predictors of Educator’s Valuing of Systematic Inquiry in Schools

2001· article· en· W47101223 on OpenAlexaffvenue
J. Bradley Cousins, Cheryl Walker

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2001
Typearticle
Languageen
FieldDecision Sciences
TopicEducational Assessment and Improvement
Canadian institutionsUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsPsychologyVariance (accounting)Relevance (law)Exploratory researchMedical educationValue (mathematics)MedicineSociologySocial science

Abstract

fetched live from OpenAlex

Abstract: This exploratory survey study of 310 educators was conducted to investigate what variables best predict educators’ attitudes toward systematic inquiry in schools. Eight variables were selected as potential predictors of educators’ self-reported views about applied research utility and relevance, their personal ability to do research, the need for teacher involvement in systematic inquiry, and teacher training in research methods. Significant proportions of the variance in the dependent variables were explained by prior participation in research and personal teacher efficacy. Years of experience teaching, perceived organizational learning capacity of respondents’ schools, and the panel in which respondents taught had modest explanatory value. Results are discussed in terms of our knowledge and understanding of teacher receptiveness to systematic inquiry in schools and implications for research and practice.

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)0.011
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.059
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.384
GPT teacher head0.507
Teacher spread0.123 · 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 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

Citations116
Published2001
Admission routes2
Has abstractyes

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