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Record W3153751796 · doi:10.1080/17565529.2021.1904811

No room to manoeuvre: bringing together political ecology and resilience to understand community-based adaptation decision making

2021· article· en· W3153751796 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 · 2021
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of OttawaGlobal Affairs Canada
FundersInternational Development Research Centre
KeywordsMaladaptationPoliticsAdaptation (eye)Psychological resiliencePolitical ecologyCommunity resiliencePower (physics)Perspective (graphical)Resilience (materials science)SociologyEnvironmental ethicsEnvironmental resource managementPolitical scienceEcologyPsychologySocial psychologyEconomicsComputer scienceBiology

Abstract

fetched live from OpenAlex

While community-led adaptation is an increasingly important subject in both academic and development circles, the politics behind adaptation decision making receives less attention. Specifically, an absence of adaptive actions is often understood as maladaptation. This study shows how incorporating lessons from political ecology such as an analysis of historically produced socio-political structures can add value to a resilience perspective by making clearer the contextual forces that shape adaptation decision making. Using the case study of urban farming in Phnom Penh, the political reality behind adaptation decision making is explored to reveal that the decision not to adapt may be a rational response to avoid risk in a situation of significant power imbalances. This understanding is important to inform the kind of policy measures and development interventions that are appropriate to support community-led adaptation.

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 score0.368
Threshold uncertainty score0.467

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 head0.042
GPT teacher head0.316
Teacher spread0.274 · 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