Bibliographic record
Abstract
Literacy is increasingly being thought of as a social practice with its use and understandings being context dependent. As an essential element within and of education, literacy offers possibilities for engaging in everyday life. Health literacy has emerged as a means to develop health-promoting practices that has meaning in social contexts. Reflecting biomedical interests, the focus of health literacy is predominately constructed as a neutral and technical process that has specific meaning and practice, positioning it as functional literacy. This paper presents one approach to critical health literacy based on a multi-dimension (3D) approach that presents literacy as a situated social practice. The 3D model will be described and then the model’s application to health literacy will be explored. The use of the 3D model to build critical health literacy challenges the biomedical approach to health literacy as solely functional literacy. Functional literacy is not sufficient for a person to build a critical social consciousness and illuminate how social determinates of health create inequitable health or how it could be ameliorated. Social justice and equity are presented as fundamental pre-requisites for health. Working with young people in context of schools, the reciprocal relationship between health and education offers space for possibilities around literacy skills and understanding about what creates health. The same space can enable young people to see opportunities for empowerment to shape and recreate their social reality. Health literacy for social justice and equity therefore has to include possibilities for understanding and responding to socio-cultural knowing.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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.
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".