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Record W2007290611 · doi:10.1080/15265161.2013.861880

Credentialization or Critique? Neoliberal Ideology and the Fate of the Ethical Voice

2014· letter· en· W2007290611 on OpenAlexaff
Stuart J. Murray, Adrian Guţă

Bibliographic record

VenueThe American Journal of Bioethics · 2014
Typeletter
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsSimon Fraser UniversityCarleton University
Fundersnot available
KeywordsProfessionalizationBioethicsIdeologySociologyManagerialismPublic relationsEngineering ethicsPolitical scienceLawSocial sciencePolitics

Abstract

fetched live from OpenAlex

In this commentary we respond to White, Jankowski, andShelton’s (2014) article about structuring a written exam-ination to assess what the American Society for Bioethicsand Humanities (ASBH) calls health care ethics consul-tation “core knowledge competencies” (ASBH 2011). Wechallenge the need for such tests and question what pur-posetheyservesavetofurtheradvanceaneoliberalversionofethics—anethicscolonizedbythecorporatistideologyof“entrepreneurialfreedomsandskillswithinaninstitutionalframework”(Harvey2005,2).Focusingonhealthcareethicsconsultants,theauthorsproposeacredentializingexamina-tion to measure ethical “core competencies” in a mannerthat would be “statistically reliable” and based on “fac-tual information, which is noncontroversial.” They furtherspeculate on “business plan development” and the “bud-getary implications” of such minutiae as multiple-choiceversus essay questions, and the outsourced costs of “psy-chometric analysis and review.” The article itself gets tan-gled in its own web of proceduralism and managerialism,ignoring the substantive ethical stakes of the litigious creeptoward the credentialization and professionalization ofbioethics.If bioethics were subject to a professional body anda standardized examination, the terms of ethical de-liberation and decision making would be sharply cir-cumscribed. “Factual” terms and procedurally verifiablepractices—arbitrarily defined—would determine in ad-vancewhatkindsofquestionscouldbeasked,inwhatway,by whom, and of whom. And under ever-increasing pres-sure to “vocationalize” curricula, educational institutionswouldaltertheirinstructionto“teachtothetest.”Aprofes-

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 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)0.035
metaresearch head score (Gemma)0.055
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.148
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0350.055
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.023
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0020.074
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 head0.107
GPT teacher head0.496
Teacher spread0.389 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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