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Record W4417023145 · doi:10.30770/2572-1852-111.3.6

Dual-Loyalty: The Wicked Problem of Corporatization in Health Professions

2025· article· en· W4417023145 on OpenAlexaff
Zubin Austin, Aly Háji

Bibliographic record

VenueJournal of Medical Regulation · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicOccupational and Professional Licensing Regulation
Canadian institutionsLeukemia & Lymphoma Society of CanadaInstitute for Work & Health
Fundersnot available
KeywordsFiduciarySafeguardingHealth careContext (archaeology)Corporate governanceAutonomyCorporatizationWicked problemBest practice

Abstract

fetched live from OpenAlex

. Increasingly, for-profit corporations are delivering a greater portion of healthcare services. While this may enhance operational efficiency and organizational effectiveness, it may raise questions about safeguarding of patients’ interests and supporting the autonomy and professional judgement of individual professionals who may work as employees. In such corporate healthcare settings, there may often be leaders who themselves are licensed professionals. These individuals may not personally provide care to patients but direct the work of other professionals or establish corporate policies, practices, and cultures that shape the practice of others. In such situations, the problem of “dual loyalties” may arise, in which licensed healthcare professionals must simultaneously reconcile a professional/ethical and fiduciary responsibility to act in the best interests of patients with a corporate responsibility to maximize shareholder value. While many different agencies—including governments, accreditation bodies, and industry agencies—participate in the regulation of corporatized healthcare, the specific responsibilities and opportunities for licensing bodies to ensure appropriate management of dual loyalties has not been widely discussed. The multi-faceted and highly interconnected nature of this wicked problem opens opportunities for discussion and reflection within licensing bodies regarding how best to use mechanisms such as Codes of Ethics, Standards of Practice, and complaints/investigation systems in the context of dual loyalties in corporatized practice settings.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.553
Threshold uncertainty score0.187

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.032
GPT teacher head0.307
Teacher spread0.275 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2025
Admission routes1
Has abstractyes

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