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Record W3172425225 · doi:10.1177/15344843211020571

Contesting “Authenticity” in Authentic Leadership through a Mad Studies Lens

2021· article· en· W3172425225 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHuman Resource Development Review · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsNorth York General Hospital
Fundersnot available
KeywordsAuthentic leadershipMental healthMental illnessPsychologyDilemmaMental distressIdentity (music)Social psychologySociologyPublic relationsPsychotherapistAestheticsPolitical science

Abstract

fetched live from OpenAlex

A Mad Studies/social model of mental distress lens was used to critique authentic leadership. We deconstructed the dilemma of authenticity and leadership by exploring how authentic leadership (dis)allows the inclusion of people with mental illness. We found that their minds are treated as disruptive and rarely ever read as authentic. For followers to view “mentally ill” leaders as authentic requires candidness, disability disclosure, and emulating norms typical to their ingroup membership. We conclude this paper by challenging HRD to rethink its stance on disruptive leadership as symptomatic of mental illness. Employees with mental health marginality can develop an authentic identity in the workplace through authenticity building experiences such as connecting mad leaders to peer-support training, offering specialized leadership development, and co-producing a mental health awareness curriculum that challenges unhealthy workplace discourses that stigmatize mad leaders and workers.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.708
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.218
GPT teacher head0.312
Teacher spread0.094 · 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