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Leading From Within

2023· book-chapter· en· W4387061043 on OpenAlexaff
Henry Dimingu, Idowu Mary Mogaji

Bibliographic record

VenueAdvances in human resources management and organizational development book series · 2023
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicManagement Theory and Practice
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsVisionPremiseTransactional leadershipPublic relationsPrismPolitical scienceEngineering ethicsSociologyPsychologyEngineeringEpistemology

Abstract

fetched live from OpenAlex

This chapter explores the concept of leadership through the prism of processes. Organizations are evolving and these evolutions may result in divergent thoughts, visions, and even actions. As a result, there is a need to develop leaders among employees who can transform these disparate thoughts and visions into something far more valuable and advantageous to organizations. Therefore, the fundamental premise of this chapter is that every employee possesses the potential for leadership, only waiting to be developed. This chapter emphasizes the need for employees to develop leadership skills. It covers what these skills are, why they are crucial to develop, and lastly, provides suggestions on how to develop employees' leadership skills.

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)0.000
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.160
Threshold uncertainty score0.534

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0080.005
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1600.104

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 head0.013
GPT teacher head0.213
Teacher spread0.201 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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