Critical Media Literacy as a Transformative Pedagogy
Bibliographic record
Abstract
Critical media literacy is important because media's ubiquitous presence has become the digital wallpaper of life, and students need to learn how to use media responsibly for learning, communicating, and participating in democratic societies. Media literacy skills have been defined historically in uncritical ways: awareness of the dangers of (over) exposure to media; the study of media as an art form; or learning about the technical elements of media such as audience. The focus of this paper is on deeper, more complex conceptions of media literacy within its complicated social and educational contexts. The authors argue that critical media literacy can provide rich learning for students. Critical media literacy builds skills of analysis and critique in the deconstruction and interpretation phase where students learn to recognize hegemonic aspects of media. Deconstruction is only one side of the critical equation, however. During the media production phase, critical media literacy can give voice to students and empower them to take action to make changes in society. In the process, critical media literacy can lead students to deeper understandings of literacies and discourses in society than previously considered possible. This paper theorizes critical media literacy in both of these phases: its deconstructive, critical phase and its transformative and critical production phase. An analysis is provided also of some of the challenges associated with critical media literacy as a transformative pedagogy.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.007 | 0.057 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".