From health education to healthy learning: Implementing salutogenesis in educational science
Bibliographic record
Abstract
AIM: The aim is to scrutinise the concept of health education (HE) and to broaden the concept of health literacy (HL) towards a lifelong healthy learning concept. HL is a broader concept than HE. This paper dissects both the health and the education concepts, and puts them into the value system of health promotion (HP) of the Ottawa Charter (OC) using the core principles and values of HP, HL, and action competence (AC) in the light of the salutogenesis (SAL). Conceptually the salutogenic model focuses on the direction towards the healthy end of the health continuum. The salutogenic theory, based on resources and comprehensibility, manageability, and meaningfulness, can be integrated into a learning model. People are seen as active and participating subjects shaping their lives through their AC. METHOD: a combination of an analysis of the values and intentions of health promotion according to the OC combined with the existing evidence on the salutogenic approach to health, stemming from a systematic research synthesis 1992-2003 and an ongoing analysis 2004-2009 by the authors. In addition, the views from a discussion with the participants of a session in the NHPR Conference 2009 are integrated. RESULTS: The similarities and differences between the salutogenesis, the OC and healthy learning were shown in a graph. Integrating the salutogenesis in educational sciences further expands the concepts of HE and HL into healthy learning. CONCLUSIONS: The results of the discussions will further develop and strengthen the concept of healthy learning.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".