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Record W7128340695

Evaluation motor activities at senior in the home enviroment and in constitutional care in East Czech lokality

2009· dissertation· cs· W7128340695 on OpenAlexaboutno aff
Leona OLIVOVÁ

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2009
Typedissertation
Languagecs
FieldSocial Sciences
TopicEducation, Psychology, and Social Research
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)CzechActivities of daily livingOlder peopleIndependent livingPaid workActive ageingQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

This thesis deals with today's trends in aging, health and physical activity. It deals with aging, its manifestation and impact ond human organism, especially considering senior population. The aim of this work is to stress out the importance of activity and of changing of habits of seniors. This work also wants to compare the activities of seniors in their home and in institutional housing in Eastern-Bohemian region. The data was aquired by quatitative research methods, by questioning. Data was collected using questionairy, by controlled interview; it was made for people over 70 years old, living in home and in retirement homes. Basic set was made from seniors (men and women) living in Eastern-Bohemian region. The sets were 100 randomly picked seniors from retirement homes and 100 randomly picked seniors living in home environment. The hypothesis, that was successfully confirmed is stated thus: Seniors are more active in their home environment. Senior living in their home were more active in sports (biking, hiking, walks, swimming) as well as in things concerning house-keeping (heating, cooking, doing the washing). They were more in touch with their family members and did activities with them. Altogether, these seniors were happier. Care for domestic animals also helps with their psyche. Seniors living in retirement homes showed great interest in RHB excercises and free-time activities conducted by the facility. As for the activity itself, retirement home seniors showed a lot less activity. This fact is due to their lifestyle in the retirement home and due to their health. By this work, I would like to address the distinction between these two groups of senior people, not only regarding activity.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.359
Teacher spread0.335 · 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.

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
Published2009
Admission routes1
Has abstractyes

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