The Collaborative Institute for Education Research, Evidence and Impact: a Case Study in Developing Regional Research Capacity in Wales
Bibliographic record
Abstract
In this case study, we describe the work undertaken since 2004 in the journey to develop a collaborative model of working aimed at building the capacity and relevance of education research and evaluation across the North Wales region. The work has culminated in 2017 with the creation of a collaborative research institute, the Collaborative Institute for Education Research, Evidence and Impact (CIEREI). CIEREI is a formal strategic collaboration between GwE (the Regional School Effectiveness and Improvement Service for North Wales), Bangor University, schools, and other bodies and institutions interested in education outcomes. The primary aim of CIEREI is to support improving outcomes for children through schools, and to contribute to teacher education and building regional capacity in school- led, co- constructed close- to- practice impact research. CIEREI's establishment is the third phase in the development of a regional research and evaluation collaboration across North Wales.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.045 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".