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Record W2885253851 · doi:10.5539/ibr.v11n9p51

Integrative Leadership Measure: Construct Development and Content Validity

2018· article· en· W2885253851 on OpenAlexvenueno aff
Sanober Salman Shaikh

Bibliographic record

VenueInternational Business Research · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Leadership and Management Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsTransformational leadershipConceptualizationTransactional leadershipPsychologyConstruct (python library)Content validityConstruct validityLeadership styleValiditySet (abstract data type)Servant leadershipReliability (semiconductor)Social psychologyComputer sciencePsychometrics

Abstract

fetched live from OpenAlex

This article aims to develop framework of integrative leadership, therefore sub objectives were set to achieve the key objective of this study. The sub- objectives of this study were to form definition, initial constructs, and items and examining the content validity of newly developed integrative leadership measure. Thorough understanding and conceptualization of the various leadership styles and their scales was achieved by the review of literature. The integrative leadership definition and its framework were built through integration of six leadership types (transformational, authentic, ethical servant, spiritual and transactional). By means of synthesizing literature on six leadership styles and asseesment of content validity, initial 13 constructs, more than 100 sub- construct and 72 items of integrative leadership were obtained. In future, researchers should focus on examining construct validity and reliability of integrative leadership.

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)0.011
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.424
GPT teacher head0.349
Teacher spread0.075 · 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 designObservational
Domainnot available
GenreMethods

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

Citations8
Published2018
Admission routes1
Has abstractyes

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