Academic and Artistic Freedom and the Israel-Palestine Conflict: Towards a Canadian Pedagogy of the Suppressed
Bibliographic record
Abstract
In this essay I argue that the suppression and discouragement of teaching and discussion relating to the Israel-Palestine conflict can and should be countered by a pedagogy rooted in the most robust traditions of academic freedom and inspired by the most challenging practices and products of artistic freedom. Freedom of inquiry, imagination, and exchange are essential to the analysis of current realities and the capacity to envisage them otherwise. This is especially true in the current chilly climate where the asymmetries of power, resources, and communicative clout are most pronounced--or, to put it more colloquially, in situations where the playing field is least level and where academic and artistic freedom are most needed and most at risk. Such asymmetrical power relations are especially evident (as well as subtly coded) in the playing out and playing off of the Israel-Palestine conflict in the United States and Canada, thanks to the intimidation, amnesia, and gross simplifications that have strengthened their hold on public discourse in both countries since 9/11 2001. The unconditional support extended to Israel by the George W. Bush administration as a key part of the so-called “war on terror” has been eagerly imitated by Stephen Harper’s government and disappointingly reinforced in November 2010 in the so-called Ottawa Protocol on Combating Anti-Semitism (O’Malley, 2010).
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.041 | 0.057 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 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".