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Record W4200070544 · doi:10.17645/up.v6i4.4536

Creating the Conditions for Climate Resilience: A Community-Based Approach in Canumay East, Philippines

2021· article· en· W4200070544 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.

Bibliographic record

VenueUrban Planning · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsMount Allison University
Fundersnot available
KeywordsVulnerability (computing)Flooding (psychology)Government (linguistics)LivelihoodPrivate sectorCommunity resilienceEnvironmental planningClimate changeGeographyPolitical sciencePsychological resilienceState (computer science)Environmental resource managementEconomic growthResource (disambiguation)EconomicsEcology

Abstract

fetched live from OpenAlex

People who reside in informal settlements in the Global South are most vulnerable to extreme weather events and their consequences, such as flooding, landslides, and fires. Those located in coastal areas face severe challenges from seasonal and typhoon-induced flooding. Research shows that uncertain land rights exacerbate community vulnerability because residents are under constant threat of eviction by private sector actors or the state. Individual and community upgrading is rarely possible in such a situation. This article focuses on the efforts to secure tenure and upgrade their community by the residents of Sitio Libis, located in Canumay East, City of Valenzuela, Philippines. The study demonstrates that while community-based approaches require skills and capacities of community members, enabling conditions created by government and/or NGOs are required for transformational outcomes. While the people of Sitio Libis did not conceptualize their efforts in terms of climate change adaptation, their success suggests the possibility for smart partnerships among state-civil society/private sector actors to emerge in support of small-scale climate action.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience 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 score0.194
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
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 head0.183
GPT teacher head0.366
Teacher spread0.183 · 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