<i>How can we Agree on Anything in This Environment?</i> Tunisian Media, Transition and Elite Compromises: A View From Parliament
Bibliographic record
Abstract
The literature on the role of the media during processes of transitions to democracy is divided over the positive or negative influence media outlets have. Both theoretically and empirically cases can be substantiated. In the case of the 2011 Arab revolts, however, there is a scholarly consensus that the media—traditional and social—have negatively affected the processes of transitions. While the criticism of the role of the media is empirically borne out, it does not explain how Tunisia was able to consolidate its democracy despite a polarizing media environment. Based on participant observation and interviews, the article argues that the inner workings of the Constituent Assembly and the role of individual deputies were crucial in overcoming a hostile atmosphere. This suggests that the role of political actors in negotiating the new rules of the game is more important than other factors shaping a transition.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.021 | 0.036 |
| Scholarly communication | 0.023 | 0.017 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".