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Record W2333274661 · doi:10.3167/fcl.2014.700108

Ethnicity without labels?

2014· article· en· W2333274661 on OpenAlex
Laura Eramian

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

VenueFocaal · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East and Rwanda Conflicts
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEthnic groupEthnographyGender studiesGenocidePower (physics)Ethnic historyIdentity (music)Class (philosophy)SociologyGovernment (linguistics)TRACE (psycholinguistics)Political scienceAnthropologyAestheticsLawLinguisticsArt

Abstract

fetched live from OpenAlex

Following the 1994 genocide, the government of Rwanda embarked on a “deethnicization” campaign to outlaw Tutsi, Hutu, and Twa labels and replace them with a pan-Rwandan national identity. Since then, to use ethnic labels means risking accusations of “divisionism” or perpetuating ethnic schisms. Based on one year of ethnographic fieldwork in the university town of Butare, I argue that the absence of ethnic labels produces practical interpretive problems for Rwandans because of the excess of possible ways of interpreting what people mean when they evaluate each other's conduct in everyday talk. I trace the historical entanglement of ethnicity with class, rural/urban, occupational, and moral distinctions such that the content of ethnic stereotypes can be evoked even without ethnic labels. In so doing, I aim to enrich understandings of both the power and danger inherent in the ambiguous place of ethnicity in Rwanda's “postethnic” moment.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.983
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.034
GPT teacher head0.314
Teacher spread0.280 · 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