Gender and Students’ Achievements: Evidence from PISA 2015
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
This study’s objective is to examine school performance gaps according to gender on a global scale. After exploitingthe data of the Program for International Student Assessment (PISA) of 2015, we can see inequalities of students’achievements between countries and within every country, by mobilizing a multilevel modelling. Resorting to thistype of modelling has allowed more robustness, as opposed to the OLS estimator, which doesn’t take data hierarchyinto consideration. Our results generally reveal that gender has a significant impact on school performance. Thus,girls perform a lot better than boys when it comes to reading, while boys perform better than girls in mathematicsand science. Our thinking and analysis are made in the context of the verification of hypotheses on a global scale, inorder to draw innovative and coherent conclusions. This contribution can also be a line of research to verify otherhypotheses that are linked to the deciding factors of inequalities of students’ achievements.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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