Liquid subjects: news media and public political pedagogy
Bibliographic record
Abstract
The purpose of this paper is to examine the relationship between news media and political education within consumer society. We argue that political education today needs to be understood as part of consumerism and media culture, in which individuals selectively expose themselves to and scrutinize various media representations not only of political issues, but also of political subjectivity and action. Individuals learn about how they might become political and act politically through their engagements with the news, in the context of the characteristics of liquid modernity, namely consumer culture, individualization, and choice. When examined through a lens of public pedagogy, political education becomes intertwined with consumer culture and the role of media in the education and socialization of political subjectivity. In this paper, we look at one example of the relationship between news and the education of political subjectivity by drawing from a larger research study, which examined the role of mainstream and alternative media in citizens’ political mobilization on climate change. We argue that news consumption is part of a public political pedagogy through which individuals negotiate becoming liquid subjects, that is, citizens who take a critical, monitorial, and individualistic consumer approach to becoming political and taking part in social change.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 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".