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Record W7135530736

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

2022· dissertation· en· W7135530736 on OpenAlexaboutno aff
Bernard Tutu Ampofo

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)ToiletPopulationStandard of livingWork (physics)Logistic regressionDescriptive statisticsMicrosoft excelSimple random sample
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.273
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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