Why is it difficult for schools to establish equitable practices in allocating students to attainment ‘sets’?
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.
Bibliographic record
Abstract
Research has consistently shown ‘ability’ grouping (tracking) to be prey to poor practice, and to perpetuate inequity. A feature of these problems is inequitable and inaccurate practice in allocation to groups or ‘tracks’. Yet little research has examined whether such practices might be improved. Here, we examine survey and interview findings from a large-scale intervention study of grouping practices in 126 English secondary schools. We find that when schools are encouraged to allocate students and move them between groups according to equitable principles by participation in a ‘best practice’ intervention, there is some increased equity of practice (i.e. a reduction in non-attainment factors used in allocation). However, the majority of schools continue to use subjective and potentially biased information to group students. Furthermore, some schools that claim to be using attainment setting appear to be using the inequitable practice of streaming. Our findings show that improvements in equity are constrained by operational and strategic factors, including timetabling, finance, and teachers’ values and beliefs relating to student ability and progression. We suggest strategies for encouraging schools to change their grouping practices, drawing on approaches for working with complex organisations.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it