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Reducción de riesgos socioambientales: Propuestas estratégicas para el desarrollo

2023· book-chapter· es· W4391624016 on OpenAlexaff
Naxhelli Ruíz Rivera

Bibliographic record

Venuenot available
Typebook-chapter
Languagees
FieldEnvironmental Science
TopicPublic Health and Environmental Issues
Canadian institutionsGovernment of Northwest Territories
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

La perspectiva para entender los desastres de origen socionatural como problemas del desarrollo de la sociedad tiene una larga data en ciencias sociales. Los muchos estudios que se han generado en las últimas cinco décadas sobre los riesgos, desastres y desarrollo han profundizado en temas como las deficiencias en capacidades institucionales, los procesos de extractivismo que influencian directamente la degradación de ecosistemas, o los procesos de desigualdad, exclusión y precarización asociados a las políticas económicas. Estos aspectos están asociados a dos condiciones propias de los riesgos socioambientales: la vulnerabilidad social y el incremento de exposición ante amenazas.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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: Other · Consensus signal: none
Teacher disagreement score0.656
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.049

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 head0.044
GPT teacher head0.304
Teacher spread0.260 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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