Global ELT coursebooks and equalities legislation: a critical study
Bibliographic record
Abstract
Equalities legislation in the United Kingdom (UK) aims to protect the rights of all residents by identifying nine characteristics that can cause discrimination. This legislation requires institutions offering programmes in English to Speakers of Other Languages (ESOL) to include positive representations of these protected characteristics in their learning content. However, many ESOL programmes draw heavily on global coursebooks—materials published for a global market—which tend to avoid equalities issues. This article describes a study that analyses global coursebooks from this UK equalities perspective, exploring how the characteristics are represented within these resources. Findings appear to suggest that the global coursebooks featured in the study are at odds with UK equalities legislation; rather than promoting diversity and inclusion, they legitimise and endorse the hegemonic normativity that fuels discrimination. We conclude the materials are an inappropriate source of core content for any ESOL programmes seeking to address the equalities agenda.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".