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Adoption of Integrated forms of Support for Family-Provided Care of Senior Citizens in a Selected Location in the Czech Republic

2013· article· en· W2066482664 on OpenAlexvenueno aff
Petra Formánková

Bibliographic record

VenueJournal of Intellectual Disability - Diagnosis and Treatment · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEducation, Psychology, and Social Research
Canadian institutionsnot available
Fundersnot available
KeywordsCzechUrban agglomerationWork (physics)BusinessHealth carePublic relationsFocus groupIntegrated careNursingPolitical scienceMedicineGeographyMarketing

Abstract

fetched live from OpenAlex

The primary focus of this paper is to outline how integrated forms of support are applied to unofficial care providers who provide care of senior citizens in the administrative region of Písek – a municipality with extended area of operation. The result of the quantitative survey provides information on how families who provide care to senior citizens in their natural home environment make use of the possibilities of professional health and social support provided in the territory of the respective self-administration entity. Also, the survey reveals what services would ease work for these unofficial care providers. The survey was done from 8/2010 to 11/2011 with 475 unofficial care providers. The outcome of the survey is the need for extending the professional services provided to smaller municipalities and rural agglomerations, so that “dead spots” in the Písek region can be filled.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.068
GPT teacher head0.394
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 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
Published2013
Admission routes1
Has abstractyes

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