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Record W2068849424 · doi:10.1215/03616878-28-2-3-195

Agency, Contract, and Governance: Shifting Shapes of Accountability in the Health Care Arena

2003· article· en· W2068849424 on OpenAlexaff
Carolyn Hughes Tuohy

Bibliographic record

VenueJournal of Health Politics Policy and Law · 2003
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAccountabilityEnthusiasmCorporate governanceAgency (philosophy)Health carePrincipal (computer security)DemocracyPublic relationsPolitical sciencePrincipal–agent problemPublic administrationBusinessSociologyPsychologyLawSocial psychologyPoliticsComputer scienceFinanceComputer security

Abstract

fetched live from OpenAlex

Current ideas about the role of the state include an enthusiasm for mechanisms of "indirect" or "third-party" governance. The health care arena, in which models of indirect governance have a long history, is an important test bed for these ideas. Classically, the arena was marked by trust-based, principal-agent relationships established to overcome information gaps. Over time (and to different degrees across nations), emphasis shifted to contractual relationships assuming relatively well-informed actors and then to performance monitoring and information sharing within complex and loosely coupled networks. In this latest stage, there is a risk that some important features of democratic leadership, and of decision making in the health care arena, will be eclipsed. Accountability mechanisms must clearly locate responsibility for actions and must allow for the exercise of professional judgment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0080.089
Scholarly communication0.0240.023
Open science0.0020.011
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0030.000

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 head0.059
GPT teacher head0.346
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), 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

Citations125
Published2003
Admission routes1
Has abstractyes

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