Palestinian resistance and international solidarity: the BDS campaign
Bibliographic record
Abstract
Israel's recent war in Gaza ('Operation Cast Lead') has both exposed Israel's defiance of international law and provided the occasion for increasing support for an organised transnational boycott, divestment and sanctions (BDS) movement. The BDS movement is aimed at challenging the Israeli state's illegal military occupation and a host of corresponding repressive policies directed at Palestinians. However, the BDS campaign, and in particular the call for an academic boycott, has been controversial. It has generated a counter-response emphasising, variously, the goals of the movement as ineffective, counterproductive to peace and/or security, contrary to norms of academic freedom and even tied to anti-Judaism and anti-Semitism. Utilising a Gramscian approach, and drawing from Charles Mills' concept of 'racial contract', we examine the history of the divestment campaign and the debates it has engendered. We argue that the effectiveness of BDS as a strategy of resistance and cross-border solidarity is intimately connected with a challenge to the hegemonic place of Zionism in western ideology. This campaign has challenged an international racial contract which, from 1948, has assigned a common interest between the state of Israel and international political allies, while absenting Palestinians as simultaneously non-white, the subjects of extreme repression and stateless. The BDS campaign also points to an alternative — the promise of a real and lasting peace in the Middle East.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".