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The Oxford Handbook of Language and Race

2020· book· en· W4251584270 on OpenAlexaboutno aff

Bibliographic record

VenueOxford University Press eBooks · 2020
Typebook
Languageen
FieldArts and Humanities
TopicHistorical Linguistics and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRacializationSociologyRace (biology)ScholarshipPoliticsRacismIndigenousGender studiesReflexivityCapitalismField (mathematics)Social sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract This handbook is the first volume to offer a sustained theoretical exploration of all aspects of language and race from a linguistic anthropological perspective. A growing number of scholars hold that rather than fixed and pre-determined, race is created out of continuous and repeated discourses emerging from individuals and institutions within specific histories, political economic systems, and everyday interactions. This handbook demonstrates how linguistic analysis brings a crucial perspective to this project by revealing the ways in which language and race are mutually constituted as social realities. Not only do we position issues of race, racism, and racialization as central to language-based scholarship, but we also examine these processes from an explicitly critical and anti-racist perspective. The process of racialization—an enduring yet evolving social process steeped in centuries of colonialism and capitalism—is central to linguistic anthropological approaches. This volume captures state-of-the-art research in this important and necessary yet often overlooked area of inquiry and points the way forward in establishing future directions of research in this rapidly expanding field, including the need for more studies of language and race in non-U.S. contexts. Covering a range of sites from Angola, Brazil, Canada, Cuba, Italy, Liberia, the Philippines, South Africa, the United Kingdom, the United States, and unceded Indigenous territories, the handbook offers theoretical, reflexive takes on the field of language and race, the larger histories and systems that influence these concepts, the bodies that enact and experience them, and finally, the expressions and outcomes that emerge as a result.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0030.005
Scholarly communication0.0070.007
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0480.013

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 head0.019
GPT teacher head0.193
Teacher spread0.174 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations275
Published2020
Admission routes1
Has abstractyes

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