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Record W2965561337 · doi:10.1080/17565529.2019.1645637

Fishing, farming and factories: adaptive development in coastal Cambodia

2019· article· en· W2965561337 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueClimate and Development · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Zones and Regional Development
Canadian institutionsUniversity of OttawaGlobal Affairs Canada
FundersSocial Sciences and Humanities Research Council of CanadaInternational Development Research CentreMinistry of EnvironmentWorld Bank Group
KeywordsLivelihoodClimate changeAdaptive capacityAgency (philosophy)AgricultureNatural resource economicsBusinessGeographyEnvironmental planningEconomicsEcology

Abstract

fetched live from OpenAlex

Climate change is threatening poverty reduction throughout the global South. One set of arguments found within the environmental change literature is that socio-ecological systems and people must have general development capacities and climate-adaptive capacities if development under climate change will be successful. This combination is known as adaptive development. The objective of this paper is to study if the emergence of a Special Economic Zone (SEZ) influences adaptive development in coastal Cambodia. Our findings are as follows: from a systems perspective, we argue that development capacities are being strengthened with SEZ employment as many employees experience an increased, predictable income, even as climate-specific capacities are weak, beyond the changes to climate exposure that people experience through migration. However, even as industrial and migration systems develop, the lack of climate-specific capacities in the urban system is concerning: water supply, land-use planning, and urban governance take little account of climate change adaptation, which may undermine longer-term development in this region. Within households, however, we see differentiation and agency, including farming households that rely on remittances from migratory SEZ labour during droughts, and local fishing households that diversify their livelihoods via nearby SEZ employment.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.034
GPT teacher head0.204
Teacher spread0.170 · 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