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Effects of Mobile Phone Use on Artisanal Fishing Market Efficiency and Livelihoods in Ghana

2011· article· en· W1612480196 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Electronic Journal of Information Systems in Developing Countries · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsLivelihoodMobile phoneBusinessFishingPhoneCommercial fishingAgricultureFisheryTelecommunicationsGeographyEngineering

Abstract

fetched live from OpenAlex

Abstract This article assesses the effects of mobile phone use on the artisanal fishing industry in the Effutu Municipality of Ghana. It contributes to the growing literature on how mobile telephony can help overcome market inefficiencies in developing countries due to imperfect information. The study shows how mobile phone use among fishermen has enhanced the efficiency of input and output markets for artisanal fishing and improved their businesses relations and livelihoods. The ‘before and after’ approach was used, based on interviews with fishermen and other supply chain actors on ways in which fishermen bought inputs and sold fish, and their perceptions of the effects of the mobile phone. The results indicate that market efficiencies improved and price variations reduced as a result of better availability of up‐to‐date information. Use of mobile phones enabled fishermen to improve their incomes, expand their markets, feel more secure at sea, and remain in closer touch with both families and other fishermen.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0000.000
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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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