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Record W7133453282

Inhabiting informal spaces in the Caribbean: A Commons-based approach to strengthen the resilience of living places to flood risks.

2024· article· fr· W7133453282 on OpenAlexaboutno aff
Fabrice Sobczak

Bibliographic record

VenueORBi UMONS · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsFlood mythResilience (materials science)TerrainPsychological resilienceRavine
DOInot available

Abstract

fetched live from OpenAlex

Cette communication explore les dynamiques d'urbanisation informelle dans les Caraïbes, notamment dans les ravines vulnérables de l'aire métropolitaine de Port-au-Prince en Haïti. Elle se concentre sur la ravine Tête de l’Eau à Pétion-Ville, où l'urbanisation non planifiée accentue les risques d'inondation et de mouvements de terrain, exacerbés par les changements climatiques. À travers une méthodologie alliant observation hodologique, arpentage de terrain et analyse des transects, la recherche propose une approche alternative aux outils urbanistiques traditionnels. En s'appuyant sur le concept des Communs (Ostrom, Monnin, Dardot et Laval) et leur application aux contextes informels, l'étude postule qu'une conscience des Communs aide à renforcer la résilience communautaire et territoriale. Les résultats attendus incluent la co-construction solidaire de territoires résilients, combinant protection écosystémique, pratiques sociales locales, et hybridation entre vivants humains et non humains.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.006
Scholarly communication0.0050.002
Open science0.0010.007
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.056
GPT teacher head0.299
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueORBi UMONSSame topicUrban and Rural Development ChallengesFrench-language works237,207