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Record W3084172955 · doi:10.1080/00083968.2020.1799830

Revisiting the host–refugee environmental conflict debate: perspectives from Ghana’s refugee camps

2020· article· en· W3084172955 on OpenAlexafffundvenue
Samuel K. M. Agblorti, Miriam Grant

Bibliographic record

VenueCanadian Journal of African Studies / Revue canadienne des études africaines · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan Campus
FundersInternational Development Research Centre
KeywordsRefugeeNegotiationPoliticsResource (disambiguation)Host (biology)Political sciencePosition (finance)Development economicsEcologyBusinessBiologyEconomicsLaw

Abstract

fetched live from OpenAlex

In the debate over refugee–host community environmental conflicts, refugees are often blamed, premised on the notion that refugees add substantially to anthropogenic activities as a result of both their demographic and socio-economic status. We employ political ecology to understand how power and economic considerations play out in the access to and use of environmental resources in Ghana’s refugee-hosting communities. Drawing mainly on qualitative data generated through group discussions and in-depth interviews, we propose an alternative position that environmental conflicts are driven by the inability of hosts to fulfil their economic interests from refugee activities. Where such economic interests are fulfilled, host–refugee environmental interactions are more likely to be devoid of conflicts even where environmental deterioration is pronounced. Negotiating how hosts and refugees collaborate in the use of, and returns from, environmental resource-related activities holds a central position in stemming environmental conflicts.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
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 head0.085
GPT teacher head0.277
Teacher spread0.191 · 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.

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

Citations10
Published2020
Admission routes3
Has abstractyes

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