Bibliographic record
Abstract
The article charts the rise of the jihadi Salafi movement in Tunisia during the transitional period and analyses the way in which the national attempt to construct a more liberal and democratic system influenced its internal dynamics and debate. It highlights in particular how democratic mechanisms and liberal norms being put in place in Tunisia impacted on the movement and how then this was reflected in its interactions with the other social and political actors in the system. The unique Tunisian environment in which democratic mechanisms and individual liberal freedoms were introduced immediately after the revolution led the jihadi Salafi movement to operate through contradictory behaviour and actions in a process of what can be called ‘stop-start’ democratic learning, which ultimately failed. The novelty of the political arrangements was beneficial to jihadi Salafism initially, as the new liberal environment allowed it to proselytise and organise in the open while railing against democracy and liberalism. In doing so they unwillingly contributed to strengthen the consensus of political actors on the necessity to build a democratic system. However, under the weight of this contradictory attitude, the movement ended up threatening the transition and failed to integrate.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".