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Record W3121054178 · doi:10.1080/19376812.2020.1870511

The contribution of non-cash remittances to the welfare of households in the Kassena-Nankana District, Ghana

2021· article· en· W3121054178 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAfrican Geographical Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsWelfareCash transfersThematic analysisBusinessCashCash flowEconomicsDemographic economicsQualitative researchFinanceSociology

Abstract

fetched live from OpenAlex

This study examined the flow of non-cash remittances in the Kassena-Nankana District in Ghana. Twenty in-depth interviews were held with recipients (respondents) of non-cash remittances and thematic analysis was used to analyze the data. Findings revealed that non-cash remittances were in the form of foodstuff and electronic appliances and they were used for various purposes. The perspectives and experiences of respondents indicate that these transfers contribute significantly to improving household welfare. Thus, establishing institutional policies to facilitate the flow of non-cash remittances will not only benefit recipients but can also contribute to the socio-economic development of receiving countries through taxation.

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.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.000
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 head0.012
GPT teacher head0.294
Teacher spread0.282 · 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