English-medium education and the perpetuation of girls’ disadvantage
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
In our community, girls do not need this [English-medium education]. Interview with male teacher Nepal is classified as a low-middle income country (World Bank, 2023), and like other such countries, it is under international pressure to attain gender equality targets in order to receive international aid. However, Nepal is also permeated by widespread perceptions that girls are subordinate to boys, which influences girls’ access to education, information, health and the labour market (Upadhaya & Sah, 2019). Women face restrictions in terms of their basic ability to ‘independently venture outside the household, maintain the privacy of their bank accounts, use mobile phones, or become employed’ (Karki & Mix, 2022: 413). Illiteracy disproportionately affects females, with 58.95% of illiterates being women and girls (UNESCO, 2021). Notwithstanding this, recent years have seen some progress in enhancing gender equality in Nepal, and females currently enjoy higher enrolment rates than males across secondary education (UNESCO, 2023). This article, however, provides evidence that the recent trend to offer English-medium education risks setting back progress made by creating a gender-differentiated system that could yield different outcomes for boys and girls and potentially restrict girls’ future trajectories post school and contribute to broader gender inequality in society.
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.
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 | 0.001 |
| 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 | 0.000 |
| 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 it