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Record W4283161481 · doi:10.1177/154805182211106063

Furthering the Metaphor of the Leadership Labyrinth: Different Paths for Different People

2022· article· en· W4283161481 on OpenAlexaff
Christina L. Stamper, Rosemary A. McGowan

Bibliographic record

VenueJournal of Leadership & Organizational Studies · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsMetaphorSociologyOrganizational identityIdentity (music)Face (sociological concept)PopulationPoliticsTypologyPublic relationsSocial psychologyGender studiesPolitical sciencePsychologySocial scienceAestheticsLaw

Abstract

fetched live from OpenAlex

Although the workforce has become more diverse, there is still a predominance of White men in positions of senior leadership. This is incongruent with social norms and values, evolving population demographics, and political movements (e.g., the MeToo and Black Lives Matter). Further, it suggests that, despite progress in shattering the glass ceiling, there may still be obstacles to senior leader roles for people who vary from the expected demographic profile. Eagly and Carli (2007a) addressed this issue for women by developing the labyrinth metaphor; however, few researchers have explored how the labyrinth and its inherent challenges might apply to others. We strive to broaden the discussion of the labyrinth metaphor, increasing its applicability, by considering two types of labyrinths—unicursal and multicursal. We also deepen the theoretical foundation by positioning the labyrinth metaphor within two prominent organizational perspectives: institutional theory and social identity theory. Relying on arguments culled from these theories, we build a typology consisting of four different categories of challenges—identity, acceptance, access, and expectations—leaders may face on their path to senior leader roles. We then explicate how these challenges create differential paths for individuals who align with the traditional leader prototype and those that do not. We believe that awareness of the underlying mechanisms of the challenges leaders may face will particularly help create solutions to these obstacles faced by individuals who are diverse in gender, race, sexuality, religion, and other important factors.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.001
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 head0.106
GPT teacher head0.248
Teacher spread0.141 · 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 designObservational
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

Citations10
Published2022
Admission routes1
Has abstractyes

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