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Record W2590600037

Estrategias para potencializar la accesibilidad de las personas con discapacidad de movilidad reducida en Las Quintas Patrimoniales del cantón Ambato

2014· dissertation· es· W2590600037 on OpenAlexaboutno aff
López Mayorga, Carlos Rolando

Bibliographic record

Venuenot available
Typedissertation
Languagees
FieldMedicine
TopicAging, Health, and Disability
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

Segun la Organizacion Mundial de la Salud – OMS (2003). Ha definido a la discapacidad como “cualquier restriccion o falta de habilidad para realizar cualquier actividad en funcion a un rango establecido como normal en la naturaleza humana. De acuerdo con la Society for Accesible Tourism Hospitality (SATH) se estima que existen en el mundo 859 millones de personas con discapacidad. La Asia-Pacific Economic Cooperation (APEC) en un estudio publicado en el ano (2003) establece que en paises como Australia, el 18% de la poblacion sufre de alguna discapacidad; en Nueva Zelanda, el 19.1%; en Estados Unidos la cifra aproximada es del 20.6%; en Canada, del 15.5%. En la Comunidad Europea se calcula viven 50 millones de personas con discapacidad, lo que representa el 14% de la poblacion. En Mexico, sin contar con un estudio expresamente dedicado a obtener el porcentaje de la poblacion que sufre de alguna discapacidad, se calcula que puede existir un 10%. APEC (2003). El Consejo Nacional de Discapacidades, CONADIS, es un organismo autonomo de caracter publico, creado en agosto de 1992, a traves de la Ley 180 sobre Discapacidades. Ejerce sus atribuciones a nivel nacional, dicta politicas, coordina acciones y ejecuta e impulsa investigaciones sobre el area de las discapacidades. Su conformacion es democratica, en la que participan todas las organizaciones publicas y privadas vinculadas directamente con las discapacidades.

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 score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.002

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 head0.021
GPT teacher head0.338
Teacher spread0.317 · 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
Published2014
Admission routes1
Has abstractyes

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