Journalism boundary work through the lens of alternative media: A comparative analysis of journalism metadiscourses in French-speaking Belgium and Brazil
Bibliographic record
Abstract
This article examines the journalism boundary work by studying the journalism metadiscourses performed by the French-speaking Belgian and Brazilian alternative media. Based on a socio-pragmatic discourse analysis, it discusses how these media legitimize their role by criticizing mainstream media and/or by claiming a set of practices considered as desirable in their contexts. The corpus consists of 64 articles collected between 2015 and 2020. The study highlights the alternative media’s strategies of expansion/inclusion and defense of autonomy, as well as their metadiscourses on advocacy journalism and audience engagement. A key finding is the populist dimension of these discourses, as both contexts reflect a desire to reconnect journalism with ‘the people’ and to maintain that alternative media are authentic representatives of public interests. In Belgium, this populism is media-centric and reformist, challenging economic structures while promoting pluralism and civic participation. In Brazil, it is more radical and ideological, expressing a deep distrust of the mainstream media for its complicity with political elites. In both cases, audience engagement is used to legitimize the role of alternative media by claiming proximity to ordinary citizens and presenting themselves as corrective – or even substitute – voices in a crisis of journalistic authority and democratic representation.
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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 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.011 | 0.018 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".