Factors leading to migration of women from the North to the South of Ghana. The case of “Kayayei” (head potters) in the market of Accra
Bibliographic record
Abstract
The goal of the study is to identify the elements that contributed to migration of women from Navrongo in North of Ghana to Accra; specifically, the case of the "Kayayei" (head porters) in the Accra central business area. The target population of the research were female migrants from Navrongo district in north of Ghana who are currently engaged in head porterage in the Accra central business district. The study used a cross-sectional design (questionnaire) to collect data from 224 respondents. Simple random sampling methods were utilised in selecting head porters at their resting camps in the course three weeks. The data from completed questionnaire were entered into Microsoft excel spreadsheet before exporting to STATA for final analysis. Descriptive analysis and logistic regression methods were used in analysing the data and the response presented in tables and figures. The main findings indicated those with no formal education, teenager and early adults, and single women were more likely or have the urge to migrate to the urban city. Pull factors identified includes better opportunities, jobs, better living standards and the zeal to earn income. The push factors were frequent conflicts and the long period of dry season at the place of origin. Majority of respondents claimed that their living standards have improved since the migrated to Accra, although over a quarter of respondents did not have a good place to sleep, majority of head porters did not have access to healthcare, toilet and bathroom facilities. Income earned from work are mostly remitted to cater for parent, siblings and children in the village of origin while some are used for personal items.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".