A review of the literature on childhood executive functions in Zambia
Bibliographic record
Abstract
Executive functions development has received a considerable amount of attention in the literature and is known to predict a range of social, cognitive and emotional outcomes in both children and adults; however, little is known about factors that contribute to its development in the Zambian context due to the fragmented literature available in Zambia. A literature review was conducted using five electronic databases (University of Zambia Institutional repository, Google scholar, PubMed, BioMed Central and EBSCO Host) to identify factors that affected executive functions in preschool and primary school children in Zambia. This review established that early childhood education, socio-economic status, physical health, and culture as factors that fall under three categories namely research, environmental and biological affect the development of executive functions among children in Zambia. This review suggests that teachers, caregivers and early childhood stakeholders in Zambia need to pay attention to both environmental and biological factors when designing executive function interventions for preschool children. A focus on improving early childhood education, nutrition, access to good quality health care, intensifying appropriate cognitive stimulating parenting and teaching practices that boost EF in public preschool and primary schools is required
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.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".