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Record W3195824695 · doi:10.1177/09562478211035644

Rights, justice and climate resilience: lessons from fieldwork in urban Southeast Asia

2021· article· en· W3195824695 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

VenueEnvironment and Urbanization · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaInternational Development Research Centre
KeywordsTransformative learningOperationalizationSociologyCorporate governancePolitical scienceClimate justiceVulnerability (computing)Resilience (materials science)General partnershipTechnocracyEnvironmental ethicsPoliticsEnvironmental resource managementEconomic growthClimate changeEcologyLawBusinessEconomics

Abstract

fetched live from OpenAlex

Recent transformative resilience research calls for urban climate interventions that better meet the needs of low-income and other marginalized groups. Such initiatives, it is suggested, must move beyond technocratic and superficial solutions to address the systems and structures that create climate vulnerability. While these are important theoretical developments, there is still much to be learned about how to support transformative resilience on the ground. This paper situates transformative resilience theory in practice with lessons from a five-year research partnership in Southeast Asian cities. We argue that for resilience research to advance rights and justice, knowledge production and mobilization efforts must be conceptualized as active parts of the transformation process. Bringing together conceptual and methodological insights from resilience, political ecology and governance learning research, we offer three pathways for transformative resilience and present examples of how they can be operationalized in Southeast Asia and beyond.

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 score0.177
Threshold uncertainty score0.370

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 head0.036
GPT teacher head0.267
Teacher spread0.231 · 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