Bibliographic record
Abstract
Media and education are social institutions that play central roles in shaping the perceptions, beliefs, values, ideological stances, and arguably even the actions of citizens. What are the relationships between these two institutions and the practices associated with each? How do media conceptualise and represent education, schools, and literacy? What educational values are highlighted within news media? In turn, how do educational practices such as media education and media literacy engage children, youth and adults to reflect on the social institution of media and its implications and effects on our lives? How are new media used by youth, and others, to resist oppression and create new kinds of educational and social spaces? Just as journalistic media tend to ignore education or to represent it in reductive terms, so do educational researchers and practitioners tend to overlook and sideline critical inquiry into media, new media practices, and media as a social institution. In all cases examined within this Special Issue, media function in contradictory roles – often entrenching self-regulation in the service to the corporatised state while simultaneously creating spaces to debate what a healthy civil society might or should be (see Atton, 2002; Beers, 2006; Carroll & Hackett, 2006) In the present issue, the three sets of articles illustrate intersections between media, public knowledge and power. The contributions explicate a continuum in which people simultaneously accept, co-opt and/or create new representations. Three central topics are addressed in this issue: (1) the effects of corporatisation and the state on media and schools, and how this impacts on individuals and collective practices of resistance; (2) media education and media literacy, including media production; and (3) media and policy making, with particular attention to standardised testing.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".