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Record W2995981043 · doi:10.29035/pai.5.2.102

Bienestar subjetivo y sus representaciones sociales en la vejez

2019· article· es· W2995981043 on OpenAlexaff
Enrique Hernández Guerson, Sandra Areli Saldaña Ibarra

Bibliographic record

VenueRevista Pensamiento y Acción Interdisciplinaria · 2019
Typearticle
Languagees
FieldMedicine
TopicAging, Health, and Disability
Canadian institutionsAlberta University of the Arts
Fundersnot available
KeywordsSociology

Abstract

fetched live from OpenAlex

ResumenInvestigación que recuperó de personas adultas mayores representaciones sociales de bienestar subjetivo sobre el envejecimiento y la vejez, que contribuye a la comprensión de estos dos procesos, desde una óptica positiva de la salud.La indagación se realizó en el marco de las heterogeneidades del envejecimiento, explicado en diferentes documentos de organismos internacionales, nacionales y de derechos humanos respecto de las personas adultas mayores.Estudio cualitativo de corte interpretativo con dos niveles de profundidad de análisis, descriptivo y analítico.El marco teórico de las representaciones sociales sirve de apoyo, para que recursos técnicos para la investigación, como lo son los testimonios y con recursos de triangulación metodológica, utilizando para tal fin la escala de satisfacción global con la vida, identificó la objetivación de las representaciones sociales del bienestar subjetivo, analizando los textos producidos con estrategias de análisis de contenido, en función de sexo, institucionalización o no, actividad actual remunerativa formal-informal o sin actividad remunerativa.El propósito de comprender los aspectos cualitativos generadores de satisfacción o no, recuperadas de la subjetividad expresada en los discursos de los participantes, para reforzar dichas condiciones de bienestar en las intervenciones de promoción de la salud y psicoeducativas que se implementen para el envejecimiento y vejez.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.008
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.353
Teacher spread0.327 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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