MétaCan
Menu
Back to cohort
Record W2029173028 · doi:10.2217/14622416.8.9.1115

Pharmacogenomics Research Involving Racial Classification: Qualitative Research Findings on Researchers’ Views, Perceptions and Attitudes Towards Socioethical Responsibilities

2007· article· en· W2029173028 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

VenuePharmacogenomics · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRace, Genetics, and Society
Canadian institutionsUniversité de Montréal
FundersNational Institute on Minority Health and Health DisparitiesCanadian Institutes of Health Research
KeywordsPharmacogenomicsThematic analysisQualitative researchScrutinyRace (biology)PopulationMedicinePsychologyEngineering ethicsMedical educationSociologyPolitical scienceSocial sciencePharmacologyEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: Racial classification of study samples has been a common practice since the early days of pharmacogenomics research. The use of race as an axis of stratification in the study of human genetic variation and population differences in drug response has come under intense scrutiny recently, particularly among policy makers, clinicians and researchers. However, there are no published empirical data on how genomics scientists perceive ethical concerns or view their own professional roles when they are confronted with this issue in their everyday practice or have to decide themselves whether racial classification should be a cornerstone of their research work. OBJECTIVES: To investigate the views and perceptions of researchers on the use of racial classification in pharmacogenomics research using a qualitative research methodology. METHODS: We interviewed genomics researchers about their perceptions on pharmacogenomics, race and science, population-based genomics research and the attendant implications for their professional duties. We sought out researchers who self-identified with many of the populations likely to be solicited for race-specific pharmacogenomics research. A thematic investigation of the semistructured interviews was undertaken using the qualitative data software program ATLAS.ti to extract and systematically analyze complex phenomena (e.g., professional viewpoints) embedded in the narratives from the interviews. RESULTS: The participants expressed the 'doubled-edged' nature of pharmacogenomics research involving racial classification while also having a cautiously optimistic view of race-based therapeutics. They believed that pharmacogenomics could improve health outcomes for racially defined populations in the context of health disparities. Sensitized to racism and potential abuses, they expressed concerns and need for precautionary measures over the sensitive nature of racially categorized research results. On the other hand, researchers perceived themselves as being responsible primarily for providing raw scientific data. CONCLUSION: Researchers engaged in genomics investigations appear to display a guarded and yet favorable perception on the utility of race in pharmacogenomics investigations. Interestingly, researchers remain sceptical of their own roles vis-à-vis ethics and delegating socioethical responsibilities to ethicists was seen as a way to remedy this shortfall instead of broadening the scope of self-governance in scientific practice to socioethical issues. While these data do not necessarily reflect views and attitudes of all scientists, future science policy questions on how best to integrate molecular genetics with race-based therapeutics and incorporation of socioethical reflection in daily practice of genomics research need to consider the perceptions of scientists and similar 'upstream control points' in the process of knowledge generation and dissemination.

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)0.028
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0280.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.449
GPT teacher head0.578
Teacher spread0.129 · 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