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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 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)0.031
metaresearch head score (Gemma)0.029
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 score0.031
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0050.038
Scholarly communication0.0150.016
Open science0.0020.007
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0020.000

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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