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Record W7028048484

Entrenamiento a los profesionales del centro de salud “Fuerte Militar Marco Aurelio Subía” en técnicas cognitivo conductuales para gestionar el estrés presente y prevenir el Síndrome de Burnout en el período de marzo – julio del 2020

2021· dissertation· es· W7028048484 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUniversidad Politécnica Salesiana Repositorio Digital (Universidad Politécnica Salesiana) · 2021
Typedissertation
Languagees
FieldMaterials Science
TopicMaterial Selection and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsBurnoutContext (archaeology)Work (physics)Order (exchange)
DOInot available

Abstract

fetched live from OpenAlex

La presente sistematización extrae experiencias respecto a la elaboración de una guía de talleres con técnicas cognitivo-conductuales que permita trabajar en los niveles altos de estrés y prevenir el síndrome de Burnout que se evidenció en los/as profesionales del Centro de Salud “Fuerte Militar Marco Aurelio Subía”. 
\nComo eje de la sistematización se hizo énfasis en las acciones ejecutadas por parte de la autora a lo largo de la elaboración de la guía.
\nEntre las técnicas planteadas en la guía se destacaron: las técnicas de relajación como: relajación diferencial variante Labrador, relajación autógena de Schultz, técnicas de relajación grounding y selfholding; reestructuración cognitiva y entrenamiento en habilidades sociales.
\nFinalmente surgieron preguntas clave a las cuales posteriormente se dio respuesta, mediante el contraste comparativo de elementos de la experiencia (sesiones, tareas, dinámicas grupales, ejercicios, etc.) que mostraron importantes tensiones productivas entre sí o diferenciación notable entre elementos que mostraban resultados o características buscadas o deseadas y elementos que no.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0030.004
Open science0.0040.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.274
Teacher spread0.264 · 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