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Record W4281977187 · doi:10.16922/wje.24.1.3

Schools as Learning Organisations in Wales: A Critical Exploration of the International Evidence Base

2022· article· en· W4281977187 on OpenAlexfundno aff
Alma Harris, Zoe Elder, Michelle Jones, Angella Cooze

Bibliographic record

VenueCylchgrawn Addysg Cymru / Wales Journal of Education · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicEducational Assessment and Improvement
Canadian institutionsnot available
FundersMcGill UniversityStrongJohns Hopkins University
KeywordsWelshEmpirical evidenceKey (lock)Evidence-based practicePublic relationsKnowledge basePolitical scienceKnowledge managementComputer scienceEpistemologyHistoryMedicineComputer security

Abstract

fetched live from OpenAlex

Within the Welsh education system, ‘Schools as Learning Organisations’ (SLOs) remains a centrepiece of current education policy. This article considers some of the key evidence base(s) that connect to and underpin the SLO model in Wales. This is not a review of the literature but rather an overview of the main empirical evidence that reinforces the SLO approach in Wales. The article highlights that there is a supportive, empirical evidence base for each of the 7 dimensions of the Welsh SLO model. It concludes, however, that more practical guidance, particularly about implementation processes, are needed to assist schools in their journey towards becoming stronger learning organisations.

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)0.060
metaresearch head score (Gemma)0.131
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.131
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0180.020
Science and technology studies0.0030.008
Scholarly communication0.0140.010
Open science0.0020.012
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.180
GPT teacher head0.463
Teacher spread0.283 · 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 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

Citations4
Published2022
Admission routes1
Has abstractyes

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