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Record W2225675407 · doi:10.3389/fpsyg.2015.01751

The Evolution of Empathy and Women’s Precarious Leadership Appointments

2015· article· en· W2225675407 on OpenAlexafffund
John G. Vongas, Raghid Al Hajj

Bibliographic record

VenueFrontiers in Psychology · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsConcordia University
FundersFonds de Recherche du Québec-Société et CultureConcordia University
KeywordsEmpathyPsychologyPerceptionScale (ratio)Social psychologyAssociation (psychology)Public relationsPolitical science

Abstract

fetched live from OpenAlex

Glass cliffs describe situations in which women are promoted to executive roles in declining organizations. To explain them, some authors suggest that people tend to "think crisis-think female." However, the root cause of this association remains elusive. Using several subfields of evolutionary theory, we argue that biology and culture have shaped the perception of women as being more empathic than men and, consequently, as capable of quelling certain crises. Some crises are more intense than others and, whereas some brew within organizations, others originate from the external environment. We therefore propose that women will be selected to lead whenever a crisis is minimal to moderate and stems primarily from within the organization. Men, on the other hand, will be chosen as leaders whenever the crisis threatens the very existence of the firm and its source is an external threat. Leadership is a highly stressful experience, and even more so when leaders must scale glass cliffs. It is imperative that we understand what gives rise to them not only because they place women and potentially other minorities in positions where the likelihood of failure is high, but also because they help propagate stereotypes that undermine their true leadership ability.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.191

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.144
GPT teacher head0.334
Teacher spread0.190 · 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 designQualitative
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

Citations32
Published2015
Admission routes2
Has abstractyes

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