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Record W6925940450 · doi:10.2390/biecoll-mhcp4-4.1

Foundations of Health Education

2019· article· en· W6925940450 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicMetal Alloys Wear and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsHealth promotionHealth educationPopulation healthHealth policySocial determinants of healthPopulationHRHISPublic health

Abstract

fetched live from OpenAlex

The module covers principles and concepts of health education, different approaches to health education, assessing population health needs, health education methods and tools, as well as how to work with individuals (counselling methods), with small groups (including self-help groups), and with population. Health education is an important tool in overall promotion of health. Health education principles are directed to healthy life style and strengthening defense mechanisms by efficient contribution of individuals in the social life. Health education is important for entire population regardless of age, educational level, gender, health and other determinants. Health education should be adjusted to the local culture needs and possibilities. Health promotion program of the World Health Organization from 1984 and Declaration from Ottawa from 1986 represent a basis for an innovative approach toward health education based on the social concept of health and healthy life styles. The new broader approach ”Education for Health” beside relevant and precise information includes all spontaneous and organized actions directed toward health. An essential precondition for those actions is to provide such healthy environment where a healthy choice would be the easiest choice. In this way the control and responsibility for someone’s health are becoming an integrative part of everyday life of the individual, family, community and society through adopting healthy life styles, and creating supportive environments for health.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.999

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)0.0060.002

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 head0.033
GPT teacher head0.302
Teacher spread0.269 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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
Published2019
Admission routes1
Has abstractyes

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