Academic voices on the health and humanitarian crises in Gaza
Bibliographic record
Abstract
Academic publications on human rights violations in Gaza surged after Israel's large-scale destruction following Hamas's 7 October 2023 attack. We analysed the uncoordinated cooperative efforts documented in these works by reviewing publications addressing the health and humanitarian crises in Gaza between October 2023 and April 2024. We present a unified academic voice advocating for recognizing and restoring human rights for the people of Gaza. In the publications, we identified three key themes: 'expression', 'emotionality' and 'expectations'. Many academics openly express how they see Israel's actions in Gaza. In line with the International Court of Justice and the UN Special Rapporteur, they believe Gaza is facing 'apartheid', 'ethnic cleansing', or 'genocide' by Israel. This understanding further takes an emotional toll on academics, as most of them feel it 'painful' to process information and write about hunger, death, destruction and isolation in Gaza. Academics express disappointment in Western political powers that enable Israel's continuing human rights violations in Gaza. At the same time, they demand that political powers take immediate measures to ensure a permanent ceasefire in Gaza and its rebuilding, as some view the UN as a 'soft' body as it is unable to enforce the ceasefire.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".