Aboriginal Adolescents, Critical Media Health Literacy, and the Creation of a Graphic Novel Health Education Tool
Bibliographic record
Abstract
As Coyote tossed his eyes the next time, the ravens swooped, swift as arrows from a strong bow. One of them snatched one eye and the other raven caught the other eye."Quoh! Quoh! Quoh'," they laughed, and flew away to the Sun-dance camp. (Quintasket, 1933)The knowledge mobilization project involving Aboriginal students described in this article is an extension of a multi-phase, longitudinal, interdisciplinary research project aimed at understanding the processes through which adolescents develop critical media health literacy (CMHL) (Wharf Higgins & Begoray, 2012; Wharf Higgins, Begoray, Beer, Harrison, & Collins, 2012). The primary purpose of this project was to create a culturally relevant CMHL health education graphic novel. An additional purpose was to develop pedagogical approaches to be used to stimulate discussion around media-perpetuated health messages with Aboriginal adolescents: Like Coyote, they too have had their eyes snatched. In brief, we collaborated with Aboriginal students to create culturally sensitive material representative of their identities as media-affected adolescents in the 21st century. In turn, the dialogic process utilized during our project appeared to be a viable pedagogical approach when working with CMHL and Aboriginal adolescents, a supposition that will be the subject of our further research in the fall of 2013. Throughout the project, the authors, all of whom are non-Indigenous, were guided in their use of Indigenous ways of knowing by the Aboriginal education community.Keywords: Aboriginal adolescent health; health education; critical media health literacy; graphic novels as health education toolsAuthor Note:The authors gratefully acknowledges the financial support of the Canadian Institues of Health Research (CIHR 293119) in the funding of this project.
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 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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".