Demography, Knowledge-Gap Effect and Exclusive Breastfeeding Campaign in Lagos and Ogun States, Nigeria
Bibliographic record
Abstract
Resistance to six-months exclusive breastfeeding remains pervasive among mothers in spite of the numerous health and economic benefits of breastfeeding. Experts attribute the nonchalance towards exclusive breastfeeding to several factors, including myths and traditional beliefs as well as fear that breastfeeding weakens the breast fibre and consequently, quickens the sagging of the breast and the woman’s sexual appeal. In Nigeria, government and non-governmental agencies continue to promote exclusive breastfeeding for the first six months of life. The purpose of this paper was to investigate the influence of socio-economic variables on the awareness, knowledge and adoption of the six months exclusive breastfeeding campaign in two Nigerian states.A mixed methods design was employed. First, a series of in-depth interviews was conducted with six health care workers in Lagos and Ogun States. Thereafter, 1500 copies of a questionnaire containing16 items were administered to a purposively drawn sample of lactating mothers whose babies fell within the age range of 0 and 12 months.The results showed a high awareness level of the six-months exclusive breastfeeding campaign. Chi Square test suggests that the socio economic status of women does not significantly influence their awareness of the six months exclusive breastfeeding (p>0.060). Similarly, respondents’ educational levels showed no significant influence on their knowledge of six months exclusive breastfeeding (p > 0.070).Contrary to the thesis of the knowledge gap communication theory, awareness does not depend on socio economic status. In all, demographics of women in Lagos and Ogun states do not influence their awareness, knowledge and adoption of six months exclusive breastfeeding.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".