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Record W2276082883 · doi:10.61520/et.203-2042015.166

TURISMO PARA TODAS LAS PERSONAS EN ESPAÑA: FUNDACIÓN ONCE GENERANDO DERECHOS

2023· article· es· W2276082883 on OpenAlexaff
Jesús Hernández-Galán, María Dolores Muñoz de Dios, Yolanda María de la Fuente Robles

Bibliographic record

VenueEstudios Turísticos · 2023
Typearticle
Languagees
FieldSocial Sciences
TopicSocial Sciences and Policies
Canadian institutionsOptech (Canada)
Fundersnot available
KeywordsPersonaHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Apoyados en el Real Decreto Legislativo 1/2013, de 29 de noviembre, por el que se aprueba el Texto Refundido de la Ley General de derechos de las personas con discapacidad y de su inclusión social, abordamos el turismo como una cuestión de derechos en defensa de las personas con discapacidad, poniendo en valor cómo el proceso evolutivo ha llevado al turismo hasta un nuevo paradigma basado en la inclusión, con independencia de las capacidades funcionales de la población.A través de la implicación por promover la accesibilidad, se muestran diferentes ejemplos de buenas prácticas a nivel nacional desdeel ámbito público-privado, destacando el compromiso de la Fundación ONCE para la cooperación e inclusión social de personas condiscapacidad, por mejorar la calidad de vida de las personas.

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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.261

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.045
GPT teacher head0.367
Teacher spread0.322 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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