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The Imprinting Perspective on the Origins of Leadership

2020· article· en· W3045520273 on OpenAlexaff
Yeun Joon Kim, Soo Min Toh, Yingyue Luan

Bibliographic record

VenueAcademy of Management Proceedings · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsImprinting (psychology)DirectiveLeadership stylePsychologyPublic relationsSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

The current research offers an imprinting perspective on the origins of leadership styles by investigating the imprinting of childhood social class on directive and empowering leaderships. With multi-wave and multi-source field data from 188 leaders at a health food company in Korea, we find that leaders from low childhood social class, relative to those from high childhood social class, tend to be imprinted with a stronger motivation to control organizational resources in the workplace. The motivation in turn relates positively to directive leadership – leader behaviors that maintain tight control over organizational resources by making elaborate plans for employee activities and allocations of budget and task materials as well as closely monitoring the executions of the plans –, but negatively to empowering leadership – leader behaviors that share the control of organizational resources with employees. In addition, the availability of organizational resources moderates the mediated relationships between childhood social class, motivation to control organizational resources, and leadership, such that the leader’s motivation to control organizational resources explains the relationship between childhood social class and the leadership behaviors only when the organization provided insufficient resources. Our research suggests childhood social class may have enduring effects on leadership styles by imprinting how leaders respond to organizational resource environments.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.130
GPT teacher head0.333
Teacher spread0.203 · 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 teacher head, not a consensus.

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

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
Published2020
Admission routes1
Has abstractyes

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