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Record W4366992995 · doi:10.1177/00380385221122432

Sociological Imaginations for Anti-Racist Futures: An Interview with Dr Prudence Carter

2023· article· en· W4366992995 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSociology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicContemporary Sociological Theory and Practice
Canadian institutionsYork University
Fundersnot available
KeywordsSociologyRacismFutures contractArticulation (sociology)PrudenceValue (mathematics)Sociological researchEpistemologySocial scienceLawPoliticsGender studiesEconomicsPolitical science

Abstract

fetched live from OpenAlex

In this interview, Dr Prudence Carter, 2021–2022 President-Elect of the American Sociological Association, discusses how sociology can contribute to anti-racist futures across national contexts. Her insights point to the need for greater self-awareness in sociology regarding race and racism, for clarification of our aims and for better articulation and translation of popularized theoretical concepts, such as structural racism, to the general public. To achieve radical inclusion in the future, she highlights the importance of engaging in public and policy sociology, by explaining and substantiating policies and practices derived from our research. She also underscores the significance and value of comparative cross-national and multidisciplinary collaborative research. Most importantly, she brings to the fore the necessity of imagining new epistemological and methodological approaches to study the conditions that will enable our societies to attain equitable and anti-racist futures. Fundamentally, this involves extending our sociological imaginations.

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.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.172
GPT teacher head0.449
Teacher spread0.277 · 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