Bibliographic record
Abstract
In sub-Saharan Africa (SSA), nearly 20% of primary school-aged children are out-of-school (OOS; UNESCO, 2019). While examining risks related to being OOS is crucial, identifying factors that help children at the highest risk of being OOS remain enrolled (defined here as educational resilience) is equally important, yet understudied. We examined child- and caregiver-level resilience factors associated with school enrollment of primary school-aged children in rural Côte d’Ivoire (N =851, Mage=9.14, SDage=2.38). Children who were educationally resilient were more likely to have caregivers who believed more strongly in teachers’ ability to impact educational outcomes. These beliefs were associated with higher levels of poverty, fostering, increased caregiver stress, and higher caregiver education. Notably, caregiver factors besides beliefs were not related to enrollment. Further, caregiver beliefs were not related to any school-level factors. Results suggest that caregiver subjective beliefs may contribute to schooling decisions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".