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Record W2099721473 · doi:10.5539/ach.v6n2p97

Institutional Health Care for the Elderly in North-eastern Thailand

2014· article· en· W2099721473 on OpenAlexvenueno aff
Ajchara Pornsema, Kosit Phaengsoi, Chanita Summat

Bibliographic record

VenueAsian Culture and History · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Elderly peoplePensionWork (physics)Health careEconomic growthGerontologyState (computer science)Private sectorVariety (cybernetics)SocioeconomicsBusinessMedicineSociology

Abstract

fetched live from OpenAlex

This qualitative research aims to assess the state of institutional health care in North-eastern Thailand. The investigation was conducted from October 2012 to October 2013. Results found that a number of elderly people are neglected by their families. The majority have difficulty moving, poor health and emotional problems. Everyday lifestyle problems are caused by inadequate exercise. Caregivers must be dedicated. Social activities are provided for elderly people, such as Old People’s Day, Mother’s Day and New Year’s Day. Most elderly people receive a pension and some supplement their income through other sources. Elderly people have a low income and a high cost of living so are required to work to support themselves. The government and private sector both support a variety of activities to promote the healthcare of elderly people in North-eastern Thailand.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.900
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.220
Teacher spread0.196 · 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 teacher head, 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".

Quick stats

Citations1
Published2014
Admission routes1
Has abstractyes

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