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Record W2944129427 · doi:10.5465/annals.2016.0108

Being Your True Self at Work: Integrating the Fragmented Research on Authenticity in Organizations

2019· article· en· W2944129427 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

VenueAcademy of Management Annals · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsMcGill University
Fundersnot available
KeywordsExtant taxonEnthusiasmEmpirical researchOrganization studiesSociologyCritical management studiesIdentity (music)Public relationsWork (physics)Power (physics)Engineering ethicsEpistemologySocial sciencePolitical sciencePsychologySocial psychologyAestheticsEngineering

Abstract

fetched live from OpenAlex

In tandem with a surge of public interest in authenticity, there is a growing number of empirical studies on individual authenticity in work settings. However, these studies have been generated within separate literatures on topics such as authentic leadership, emotional labor, and identity management, among many others, making it difficult for scholars to integrate and build on the authenticity research to date. To facilitate and advance future investigations, this article reviews the extant empirical work across 10 different authenticity constructs. Following our research review, we use a power lens to help synthesize our major findings and insights. We conclude by identifying six directions for future research, including the need for scholars to embrace a multifaceted view of authenticity in organizations. Overall, our review both reinforces and tempers the enthusiasm in contemporary discussions of authenticity in the popular and business press.

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)0.005
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: Empirical
Teacher disagreement score0.789
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.134
GPT teacher head0.455
Teacher spread0.321 · 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