Spatial and temporal patterns in primary school enrolment and exam achievement in Rural Uganda
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
Using a mixed-methods approach, including qualitative, quantitative and Geographic Information Science methods, we assessed the primary school landscape around a protected area in Western Uganda. Data from a household survey, interviews and standardized school examinations were mapped to visualize spatial patterns in enrolment and academic achievement. We found children on average were starting school at age nine, but started to dropout as early as age 14; especially orphaned boys. Twenty of 36 schools demonstrated improving examination results from 2004 to 2013, although in one district improvements were lacking. Girls traditionally perform poorer than boys on exams in Uganda, but we found girls’ exam scores were catching-up. Support from one non-governmental organization with a long-term local presence was improving academic achievement. The use of Geographic Information Science provided spatially explicit recommendations to guide local policy actions for primary school education.
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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 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