Media literacy education in action : theoretical and pedagogical perspectives
Bibliographic record
Abstract
Foreword, David Buckingham Introduction Belinha S. De Abreu and Paul Mihailidis Part I: Media Literacy: Past and Present 1. Media Literacy: An Incomplete Project Julian McDougall 2. Voices of Media Literacy Tessa Jolls and Dee Morgenthaler 3. Media Literacy Education in Ontario Neil Andersen Part II: Digital Media and Learning 4. A Case for Curation as a Media Literacy Imperative for Participatory Culture Paul Mihailidis 5.Lessons Learned from Amanda Baggs: Implications for New Media Literacies Education Margaret Hagood 6. Visualization as a New Media Literacy Erin Reilly 7. The World is a Village: Conceptualizing Uses of New Media in Flat Classrooms William Kist Part III: Global Perspectives 8. Towards a European Network for Media Literacy: A Nordic Perspective on Challenges in a Global Society Per Lundgren 9. Media Literacy through Arts Education in Australia Michael Dezuanni and Annette Woods 10. Sowing the Seeds of Digital and Media Literacy in Lebanon and the Arab World: The Importance of a Locally Grown and Sustainable Curriculum Jad Melki 11. Hong Kong Media Education in the Web 2.0 Era: Engaging with the Net Generation Alice Lee Part IV: Public Spaces 12. Towards the Integration of Media and Information Literacy: A Rationale for a 21st Century Approach Marcus Leaning 13. A Promising Future: U.S. Public Libraries as Informal Media Literacy Educators Denise Agosto and Rachel M. Magee 14. School Libraries, Media Literacy and the Potential for Civic Engagement Gayle Bogel 15. Why Media Arts Curriculum Standards Could Improve Media Arts and Critical Media Literacy in K-12 Settings Amy Petersen Jensen Part V: Civic Activism 16. What Are We Really Teaching?: Outline for an Activist Media Literacy Education Katherine G. Fry 17. Should I Really Kill My Television?: Negotiating Common Ground Among Media Literacy Scholars, Educators, and Activists Lori Bindig and James Castonguay 18. Shrinking the Divide: Solving Social Inequalities Through Media Literacy Education Nick Pernisco 19. Game-based Civic Learning in Public Participation Processes Eric Gordon and Steven Schirra Part VI: Policy and Digital Citizenship 20. On the Difficulties of Promoting Media Literacy Sonia Livingstone and Yin-Han Wang 21. Media Literacy Education: A Requirement for Today's Digital Citizens Frank Gallagher 22. Emerging from K-12 Future Shock: How to blend digital and media literacy into the Common Core Standards Rhys Daunic 23. Grasping the Complexities of U.S. Educational Policy and the Classroom: How to Move Media Literacy Education Forward Belinha S. De Abreu Part VII: Future Connections 24. Media Literacy Preparation in Undergraduate Teacher Training: An American and Australian Perspective David M. Considine and Michael M. Considine 25. Rhetoric in a New Key: Media Literacy Education for the 21st Century University Gretchen Schwarz 26. International Media and Informational Literacy: A Conceptual Framework Art Silverblatt, Yupa Saisanan Na Ayudhya, and Kit Jenkins
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.026 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.016 | 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".