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Record W4380905250 · doi:10.1007/978-3-031-17203-8_29

Global Leadership as a Driver of Entrepreneurship: A Cultural Group Market Perspective

2023· book-chapter· en· W4380905250 on OpenAlexaboutno aff
Raushan Gross

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsEntrepreneurshipFollowershipPerspective (graphical)PhenomenonInterpretation (philosophy)Entrepreneurial leadershipEntrepreneurial orientationPublic relationsPolitical scienceSociologyEpistemology

Abstract

fetched live from OpenAlex

This chapter presents the effects of leadership and fellowship on individuals and cultural groups’ entrepreneurial market perspectives. Entrepreneurial leadership is a complex phenomenon especially in the crosscurrents of marketplace spontaneous interactions and culture. Indeed culture, in its various levels and degrees, causes for interpretation may or may not hold universal applicability. Therefore, the author approaches the topic of entrepreneurship at one or two levels of analysis—cultural, leadership, innovative behavior, and firm-level entrepreneurial orientation—are explored in the preceding paragraphs. Entrepreneurial leadership initiates the opening up of economic opportunities that offer nascent and incumbent entrepreneurs following ability in the same or similar marketplaces in the long run. Entrepreneurial leadership as a concept needs further examination as to its effects on followership and culture more broadly. Quantitative analyses were used to understand these factors in entrepreneurial leadership causes and consequences in North American and Canadian marketplaces.

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)0.001
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.051
GPT teacher head0.256
Teacher spread0.204 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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