Inclusiveness in texts in the EFL classroom : A study of English teachers’ inclusion of different parts of the world in texts used in the lower grades
Bibliographic record
Abstract
This essay investigates if texts featuring different parts of the world are present in the English as a Foreign Language classroom for grades 1-3 of Swedish primary school. The focus in the essay is to investigate what texts teachers use in the English classroom and what content the texts feature related to different parts of the world. The data was collected by a combined method of a quantitative and a qualitative study with the field of English as an International Language as an area of focus. The quantitative study consisted of an online survey which received 72 replies from primary school teachers and a case study was conducted at one school with two teachers which featured both interviews and an analysis of teaching material. The online survey shows that content featuring different parts of the world is common, even if there is a bias towards the so called Inner Circle of English speaking countries of Great Britain, USA, Australia and Canada while the rest of the world is not as commonly represented. However, this depends on the material used, as the case study did not share this clear bias towards the Inner Circle and the difference was not as clear.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".