Bibliographic record
Abstract
Ideologically Challenging Entertainment (ICE) is entertainment that challenges ‘us vs. them’ ideologies associated with radicalization, violent conflict and terrorism. ICE presents multiple perspectives on a conflict through mainstream entertainment. This article introduces the theoretical underpinnings of ICE, the first ICE production and the audience responses to it. The first ICE production was Two Merchants: The Merchant of Venice adapted to challenge ideologies of the Arab-Israeli Conflict. A mixed-methods study of audience responses explored whether this production inspired audiences to shift their ideological views. Each performance included two versions of the adaptation: a Jewish dominated society with an Arab Muslim minority, contrasted with an Arab Muslim dominated society and a Jewish minority. A mixed-methods study of audience responses explored whether this production inspired audiences to shift their ideological views to become more tolerant of differences away from ideological radicalization. Of audience members who did not initially agree with the premise of the production, 40% reconsidered their ideological views, indicating increased tolerance, greater awareness of and desire to change their own prejudices. In addition, 86% of the audience expressed their intention to discuss the production with others, thereby encouraging critical engagement with, and broader dissemination of the message. These outcomes suggest that high quality entertainment – as defined by audience responses to it - can become a powerful tool in the struggle against radicalised ideologies.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".