MétaCan
Menu
Back to cohort

Plural Leadership in Health Care Organizations

2016· book· en· W2480897558 on OpenAlexaff
Viviane Sergi, Mariline Comeau-Vallée, Maria Lusiani, Jean‐Louis Denis, Ann Langley

Bibliographic record

VenueOxford University Press eBooks · 2016
Typebook
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversité de MontréalHEC Montréal
Fundersnot available
KeywordsPluralHealth careTransactional leadershipAgency (philosophy)LegitimacyPublic relationsTheme (computing)Shared leadershipTransformational leadershipSociologyPolitical sciencePsychologyLinguisticsSocial sciencePoliticsComputer science

Abstract

fetched live from OpenAlex

Because of their complex structures and cultures characterized by interaction among multiple professional and occupational groups with diverse sources of authority, expertise and legitimacy, health care organizations are prime sites for forms of collective or plural leadership. In this chapter, we describe and provide empirical examples of four different forms of plural leadership occurring in and around health care organizations. The presentation of the various forms and their empirical illustrations reveals that different situations may call for different forms and modalities of plural leadership both inside and across these organizations. However, a common theme underlying all the examples and forms is the paradoxical importance of individual agency in enabling the construction of effective forms of plurality. We conclude by discussing some of the challenges associated with these forms of plural leadership and by identifying areas for future study of their role and effectiveness in health care 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 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)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.010
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.023
Scholarly communication0.0100.004
Open science0.0010.006
Research integrity0.0010.003
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 head0.039
GPT teacher head0.196
Teacher spread0.157 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueOxford University Press eBooksSame topicManagement and Organizational StudiesFrench-language works237,207