Bibliographic record
Abstract
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 predetermined, 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 does the volume position issues of race, racism, and racialization as central to language-based scholarship, but it also examines 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-US 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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".