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RACE, SCIENCE AND A NOVEL: AN INTERDISCIPLINARY DIALOGUE

2007· article· en· W2084488603 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDeveloping World Bioethics · 2007
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of VictoriaDalhousie University
FundersUniversity of British ColumbiaDalhousie UniversityUniversity of Victoria
KeywordsDestiny (ISS module)Environmental ethicsSociologyDisciplineRace (biology)EpistemologySociobiologySocial scienceGender studiesAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

In the novel Racists by Kunal Basu (2006), two competing scientists initiate an experiment that they believe will prove which race is superior. The research subjects, one white and one black infant, are sequestered on an isolated island in the care of a mute nurse. The contest must be waged in a 'natural laboratory' with no artificial interventions and with the prospect that one will die at the hands of the other. The politics of empire, the slave trade and the advent of a new scientific way of viewing life, Darwinism, set the stage for the fictional experiment, but the ramifications of such thinking extend into the present. Coming from the disciplines of nursing, philosophy and science, we discuss how a novel can illuminate the moral dimensions of science and healthcare. The critical distance afforded by the novel provides a rich terrain for the examination of issues such as race, care and the purity of science. Despite the recent dominance of social explanations of race, science requires the examination of the differences between human beings at the biological level. The view that biology is destiny is a powerful one with dangerous consequences, especially since the belief that certain human beings' destinies are far worthier than others is a corollary of such a view. In this paper, we present the cross-disciplinary conversation, which has been facilitated by this novel. We hope this will inform ethics educators of the rich potential of using fiction as a pedagogical tool.

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)0.050
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.669
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0500.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.004
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.007
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 head0.214
GPT teacher head0.558
Teacher spread0.343 · 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