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Record W2027056068 · doi:10.5539/enrr.v5n2p81

Urban Growth and Livelihood Transformations on the Fringes of African Cities: A Case Study of Changing Livelihoods in Peri-Urban Accra

2015· article· en· W2027056068 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.

venuePublished in a venue whose home country is Canada.
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

VenueEnvironment and Natural Resources Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsLivelihoodBusinessAgricultureEnvironmental planningResource (disambiguation)UrbanizationUrban planningGeographyEconomic growthNatural resource economicsEconomicsEcology

Abstract

fetched live from OpenAlex

In recent times, a growing body of research has drawn attention to the changing interface and interdependence between urban and rural spaces in Africa. This includes studies on physical, environmental, socio-demographic, economic and other transformations in the peri-urban zone. However, little is known about how residents of peri-urban communities adapt their livelihoods to these transformations. Using the case study approach, and by applying the sustainable livelihood framework as an analytical tool, we have explored the livelihood strategies adopted by the residents of four communities in peri-urban Accrain response to the city’s physical expansion. We find that urban growth has differential effects on peri-urban livelihoods, thereby creating winners and losers. Some residents, by reason of their possession of, or control over, various forms of livelihood assets, are able to utilize opportunities offered by urban growth to devise livelihood strategies to enhance their wellbeing. Those who suffer adverse effects are mainly resource-poor farm households who, apart from not having the wherewithal to take advantage of opportunities created by urban growth, lose their farm-based livelihoods as a result of the conversion of land from agricultural to non-agricultural uses. We therefore recommend that local government authorities should incorporate peri-urban livelihood issues into their planning activities.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.311

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.076
GPT teacher head0.316
Teacher spread0.240 · 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