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Record W7131253231 · doi:10.63878/qrjs831

RECONCEPTUALIZING ETHICAL LEADERSHIP WITHIN NEO-CHARISMATIC LEADERSHIP THEORETICAL PERSPECTIVE: IMPLICATIONS FOR BUSINESS ETHICS AND ORGANIZATIONAL PRACTICE

2025· article· W7131253231 on OpenAlexfundno aff
Dr. Nabegha Mahmood

Bibliographic record

VenueQualitative Research Journal for Social Studies · 2025
Typearticle
Language
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsnot available
FundersUniversity of Calgary
KeywordsEthical leadershipAccountabilityBusiness ethicsLeadership studiesCorporate social responsibilityBusiness practiceEthical decisionSocial responsibilityLeadership style

Abstract

fetched live from OpenAlex

This literature review combines sightings from more than a few academic fundamentals on ethical leadership comparing it with neo-charismatic leadership theories, and commenting on its implications for possible organizational outcomes and practices. It reconnoiters how ethical leadership is conceptualized and operationalized, drawing its progression through manifold theoretical standpoints. The study also draws linkages with key constructs such as corporate social responsibility (CSR), social entrepreneurship, entrepreneurship, and social entrepreneurship. Additionally, it highpoints the role of essential ethical principles such as transparency, integrity or veracity, and accountability in handling ethical policymaking within organizations. The evaluation accomplishes by observing models for socially accountable and maintainable business practices that poise ethical influence with profitability. Finally, this review aims to provide a holistic understanding of the current state and future guidelines of ethical leadership in business and social initiative 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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.173
metaresearch head score (Gemma)0.783
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch, Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.937
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1730.783
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0220.017
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0020.010
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 head0.904
GPT teacher head0.721
Teacher spread0.183 · 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

Labeled directly by 2 models reading the full record.

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

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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