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Record W1976633363 · doi:10.1080/13600830902814992

Politicking the personal: examining academic literature and British National Party beliefs and wishes about intimate interracial relationships and mixed heritage

2009· article· en· W1976633363 on OpenAlexaffabout
Mike Sutton, Barbara Perry

Bibliographic record

VenueInformation & Communications Technology Law · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsUniversity of Ontario Institute of Technology
Fundersnot available
KeywordsSociologyContext (archaeology)CriminologyHatredWhite (mutation)Media studiesLawPoliticsPolitical scienceHistory

Abstract

fetched live from OpenAlex

Drawing heavily on our earlier work in this area (Perry and Sutton 2006 Perry, B. and Sutton, M. 2006. Seeing red over black and white: Popular and media representations of interracial relationships as precursors to racial violence. Canadian Journal of Criminology and Criminal Justice/Revue Canadienne de criminology et de justice penale, 48(6): 887–904. [Web of Science ®] , [Google Scholar]; forthcoming Perry, B. and Sutton, M. Forthcoming. “Crossing the line: Discourses on intimate interracial relationships in the US and UK”. In Sticks and stones: Writings and drawings on hatred, Edited by: Poynting, S. and Wilson, J. Sydney: Sydney Institute of Criminology and Federation Press. [Google Scholar]), this article discusses the issue of intimate interracial relationships (IIRs) within the context of the UK Government's current concerns with social cohesion and provides an overview of the literature on hate and prejudice against those in IIRs in the UK and USA. Following an examination of the official statistics and the numbers of mixed race people in England and Wales, we move on to provide a brief but disturbing glimpse of what it would mean if the BNP's long-term dream of winning a national election were actually to happen in light of their official website published proposed policies against IRRs and mixed heritage people.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.065
GPT teacher head0.356
Teacher spread0.291 · 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.

Study designTheoretical or conceptual
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
Published2009
Admission routes2
Has abstractyes

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