Exploring critical media health literacy (CMHL) in the online classroom
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Critical media health literacy (CMHL) is concerned with identifying healthrelated messages in the media, acknowledging the potential effects on health behaviours, critically analyzing the content of the message, and the subsequent application of the message to one’s health behaviours (Levin-Zamir & Bertschi, 2018). This exploratory research examined the CMHL skills of students (n = 120) in an entry-level, online asynchronous health and wellness course, by examining their ability to think critically about health-related themes presented in news media articles online and apply course-based knowledge during a Twitter event. Employing a content analysis of tweets from the event, students were found to illustrate CMHL skills when interacting with peers on Twitter, more than when directly assessing online news media. The findings suggest that the course curriculum be altered to include CMHL skills, to better equip students with the ability to identify accurate health information in the media.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it