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Record W3166109226 · doi:10.1016/j.ijer.2021.101810

Climates of trust, innovation, and research use in fostering evidence-informed practice in French schools

2021· article· en· W3166109226 on OpenAlex
Marie Gaussel, Stephen MacGregor, Chris Brown, Lucile Piedfer-Quêney

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Educational Research · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicEducational Assessment and Improvement
Canadian institutionsQueen's University
Fundersnot available
KeywordsContext (archaeology)PerceptionPublic relationsPedagogyPsychologySchool climatePolitical scienceSociology

Abstract

fetched live from OpenAlex

In France as elsewhere, various arguments suggest that evidence-informed practice (EIP) in education may positively impact student outcomes. However, while these arguments are beginning to mature in countries such as England, uptake of EIP theories in the French context is still nascent. The study presented in this paper seeks to address this knowledge gap. Findings suggest that French school staff generally believe that research evidence could inform educational practices as well as school organization at large. A trusting environment was positively associated with positive perceptions of EIP, but it is relatively less important than a school climate that encourages and supports research use. An interesting challenge for school leaders is how to establish cultures of research use and of innovation.

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.

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)0.022
metaresearch head score (Gemma)0.263
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.263
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.004
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.641
GPT teacher head0.660
Teacher spread0.019 · 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