DECLARATIONS OF INTERDEPENDENCE: HOW MEDIA LITERACY PRACTICES ARE DEVELOPED, NEGOTIATED, REJECTED, AND EXPLOITED ACROSS SOCIAL MEDIA PLATFORMS
Bibliographic record
Abstract
The primary goals of media literacy are laudable: active and critical thinking about the messages we receive and the messages we create. In practice, media literacy standardizes limited ways of knowing and normalizes built-in biases. Subsequently, its narrow emphasis on skill development, particularly the role of fact-checking, content creation, and independent research are all practices that can be exploited, oftentimes leading to the amplification of misinformation. Homogeneous media literacy also assumes that platforms are neutral – codifying a dominant, neoliberal, racist lens as a competency. Social media literacy in particular assumes the norms of proprietary algorithms, arming users with the skills determined by Silicon Valley’s corporate, individualist, white supremacist values. Contemporary high school curricula teaches students to ably brand and promote themselves; adept meme creators are rewarded for racial appropriation and fungible performances of Blackness; vanity metrics foster reputation anxiety in social media’s ‘success theatre’; personal data protection is an arguably futile lesson in privacy that preaches paranoid gated communities; fascist media pundits easily exploit conservative media literacy practice of “doing your own research” to naturalize misinformation. What are the implicitly raced, classed norms of reading "correctly"? What are mundane emancipatory reading practices? What alternative literacy practices do users deploy to reject these individualistic, racist standards? What does interpretive media literacy look like? This panel offers a portrait of what’s missing in media literacy and explores visions of interdependent practices that offer alternative methods of active and critical thinking about the messages we receive and the messages we create.
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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 | 0.029 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.065 |
| Scholarly communication | 0.027 | 0.034 |
| Open science | 0.002 | 0.017 |
| 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".