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Record W2116064712 · doi:10.1207/s15327019eb1002_03

Value-Based Leadership in Organizations: Balancing Values, Interests, and Power Among Citizens, Workers, and Leaders

2000· article· en· W2116064712 on OpenAlexaff
Isaac Prilleltensky

Bibliographic record

VenueEthics & Behavior · 2000
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsHarmony (color)Value (mathematics)Power (physics)Public relationsPromotion (chess)Social psychologySociologyPsychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

The purpose of this article is to introduce a model of value-based leadership. The model is based on tensions among values, interests, and power (VIP); and tensions that take place within and among citizens, workers, and leaders (CWL). The VIP-CWL model describes the forces at play in the promotion of value-based practice and formulates recommendations for value-based leadership. The ability to enact certain values is conditioned by power and personal interests of communities, workers, and leaders of organizations. People experience internal conflicts related to VIP as well as external conflicts related to disagreements with the CWL. Value-based practice is predicated on the ability to alleviate these tensions. Leaders have 4 main roles in promoting value-based practice: (a) clarify values, (b) promote personal harmony among VIP, (c) enhance congruence of VIP among CWL, and (d) confront people and groups subverting values or abusing power to promote personal interests.

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)0.006
metaresearch head score (Gemma)0.005
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 score0.013
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.022
Scholarly communication0.0130.007
Open science0.0010.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.207
GPT teacher head0.431
Teacher spread0.224 · 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

Citations100
Published2000
Admission routes1
Has abstractyes

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