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Caracterización de modelos de comunicación digital en organizaciones del tercer sector

2019· article· es· W2941290076 on OpenAlexaboutno aff
Alicia Inés Zanfrillo, María Antonia Artola

Bibliographic record

VenueVisión de Futuro · 2019
Typearticle
Languagees
FieldSocial Sciences
TopicPublic Health and Social Inequalities
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Los cambios establecidos por la Carta de Ottawa en la conceptualización de la salud pública sustituyeron estrategias de prevención de riesgos por otras de promoción centradas en el desarrollo de competencias. Contribuir a una mejor calidad de vida de las personas bajo condiciones sociales, políticas y económicas favorables implica asegurar los medios necesarios para un mayor control sobre las decisiones de salud con participación intersectorial conformada por diversas organizaciones. El objetivo del trabajo consiste en reconocer los modelos comunicativos en organizaciones vinculadas con la salud del Tercer Sector de la ciudad de Mar del Plata (República Argentina) en la actualidad. Sobre la población en estudio se adopta una metodología cuantitativa, descriptiva, que revela estrategias ancladas en la prevención, de carácter determinista, vertical, basadas en la difusión de contenidos y escasamente orientadas hacia la construcción colectiva de pautas de comportamiento que permitan concientizar sobre los factores contributivos al bienestar psico–bio-social.

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)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0020.005
Scholarly communication0.0110.009
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0160.001

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 head0.014
GPT teacher head0.312
Teacher spread0.298 · 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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