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Intervención de apoyo psicológico en dos comunidades en situación de emergencia

2021· article· en· W3199400788 on OpenAlexaff
Ana Esther Escalante Ferrer, Bremya Olyva Jahen Jiménez, Margarita Sarahí Martínez Rodríguez

Bibliographic record

VenueInventio · 2021
Typearticle
Languageen
FieldPsychology
TopicStress and Burnout Research
Canadian institutionsCegep de Sept Iles
Fundersnot available
KeywordsIntervention (counseling)SolidarityPsychologyPsychological resilienceResilience (materials science)PopulationHumanitiesPolitical scienceSociologySocial psychologyPsychiatryDemographyArt

Abstract

fetched live from OpenAlex

After an earthquake, attention to the emotional health of those affected becomes necessary. This article reports the psychological intervention carried out by squad members from the Universidad Autónoma del Estado de Morelos (UAEM) after the earthquake of September 19, 2017. The intervention helped to develop the resilience of the affected people and communities that were assisted. The participants generated individual strategies that, altogether, allowed them to recognize what they had and what was lost as a consequence of the earthquake, as well as to appreciate what they have and, based on identifying that situation, carry on with their plans, set new goals and take appropriate decisions for themselves and for their community. The capacity to respond, in a solidarity and organized manner, of the psychologists in training and graduates from UAEM to meet the demand of the civilian population in crisis situations is highlighted.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.394
Teacher spread0.362 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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