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Record W4383754556 · doi:10.56687/9781529213621

White But Not Quite

2022· book· en· W4383754556 on OpenAlexaff
Ivan Kalmár

Bibliographic record

VenueBristol University Press eBooks · 2022
Typebook
Languageen
FieldSocial Sciences
TopicDecolonial Thought and Epistemologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWhite (mutation)BiologyGenetics

Abstract

fetched live from OpenAlex

Since the ‘migration crisis’ of 2016, long-simmering tensions between the Western members of the European Union and its ‘new’ Eastern members – Poland, the Czech Republic, Slovakia, and Hungary – have proven to be fertile ground for rebellion against liberal values and policies. In this startling and original book Ivan Kalmar argues that Central European illiberalism is a misguided response to the devastating effects of global neoliberalism, which arose from the area’s brutal transition to capitalism in the 1990s. Kalmar argues that dismissive attitudes towards ‘Eastern Europeans’ are a form of racism and explores the close relation between racism towards Central Europeans and racism by Central Europeans: a people white but not quite.

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)0.002
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 score0.024
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0090.007
Scholarly communication0.0060.006
Open science0.0000.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0240.010

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 head0.045
GPT teacher head0.256
Teacher spread0.211 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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