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Record W2152303419 · doi:10.18733/c35p41

Universities in Opposition to Israel’s Military Occupation and the De-development of the West Bank and Gaza

2011· article· en· W2152303419 on OpenAlexvenueno aff
Keith Hammond

Bibliographic record

VenueCultural and Pedagogical Inquiry · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
FundersScience and Engineering Research Board
KeywordsPolitical scienceOpposition (politics)LawSanctionsHuman rightsEconomic JusticeExcusePoliticsInternational law

Abstract

fetched live from OpenAlex

This paper argues that the violation of justice in Palestine began in 1948 and was deepened in 1967 with the further occupation and de-development of Palestine which continues to this day. For forty two years, international law has been defied by Israel with one excuse after another that few people accept. Israel has persistently built more and more settlements and separations that make the basic human right to education and health near impossible for the Palestinians. Whilst international aid has been necessary, it has been politically ineffective in halting the capture and annexing of more and more Palestinian land. More Palestinians are removed from Jerusalem every day as violence upon violence is piled on the people of Palestine. This paper argues that this is unacceptable for the international family of higher education. It argues that universities around the world should take a political lead in response to the call from Palestinian and other peace workers to build the Boycott, Disinvestment and Sanctions movement in global civil society. This paper moves the position that history has built up to a point where justice for Palestine is now an undeniable global issue for people of conscience everywhere. The situation is such that universities cannot step back and leave it to politicians. Academics and students must speak out and take a lead in ending the day to day abuse of basic Palestinian rights.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score0.256

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.468
GPT teacher head0.414
Teacher spread0.054 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2011
Admission routes1
Has abstractyes

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