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Praise for Islam on <i>Campus: Contested Identities and the Cultures of Higher Education in Britain</i>

2020· other· en· W4398189496 on OpenAlexaboutno aff
Alison Scott‐Baumann, Mathew Guest, Shuruq Naguib, Sariya Cheruvallil-Contractor, Aisha Phoenix

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPraiseIslamReligious studiesSociologyReligious educationArtTheologyPhilosophyLiteraturePedagogy

Abstract

fetched live from OpenAlex

‘Islam on Campus is a very important and impressive book that will be vital reading for those interested in the civic and public role of universities, decolonisation of the curriculum, the study of Islam within western systems of knowledge, the nature and implications of the reach of the security agenda across public life, and the terms of debate over gender and Islam. Throughout it provides fresh thinking on often stale-mated debates on gender equality, freedom of speech and religious accommodation, and responses to security risks, and in ways that draw on rather than suppress critical debate.’ ‘This ground-breaking work explores the crucial topics of Islamophobia and its impact on Muslim students, and it also explores how the securitisation of Muslims on campus has transformed campus life itself, significantly restricting both freedom of expression and freedom of association. This book will be necessary reading for both sociologists of religion and Islam, and legal and political theorists interested in law and religion in liberal democracies generally.’

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0110.012
Scholarly communication0.0070.003
Open science0.0000.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.002

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 head0.017
GPT teacher head0.352
Teacher spread0.334 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2020
Admission routes1
Has abstractyes

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