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Record W4297681408 · doi:10.22136/est20221903

Vulnerabilidad sociohidrológica y capacidad adaptativa en la Alcaldía Cuajimalpa en la Ciudad de México

2022· article· es· W4297681408 on OpenAlexaff
Miriam Alfie-Cohen, Flor Yunuen García-Becerra, Mario Alberto Salinas-Toledano, Javier Reyes-Pérez

Bibliographic record

VenueEconomía Sociedad y Territorio · 2022
Typearticle
Languagees
FieldEnvironmental Science
TopicMexican Socioeconomic and Environmental Dynamics
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsHumanitiesGeographyPolitical scienceArt

Abstract

fetched live from OpenAlex

La Ciudad de México (CDMX) enfrenta una situación de vulnerabilidad sociohidrológica (SHV) debido a la creciente escasez de agua. Este estudio evalúa la SHV de la Alcaldía de Cuajimalpa con base en la construcción social del espacio. El estrés hídrico y la capacidad adaptativa son elementos clave para comprender las condiciones materiales, ambientales y sociales de un territorio. Se propone una metodología mixta como eje de acción. El artículo enfatiza la importancia del conocimiento de la vulnerabilidad socio-hidrológica en zonas específicas como herramienta para comprender la dinámica espacial y la particularidad territorial.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.002

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 head0.006
GPT teacher head0.223
Teacher spread0.217 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations1
Published2022
Admission routes1
Has abstractyes

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