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Breaking Barriers. Understanding the Work Experiences of Neurodivergent Employees

2025· article· en· W4416005078 on OpenAlexaffabout
Kerstin Alfes, Thomas Blondel, Daniela Lup, Sabrina D. Volpone, Joanna Maria Szulc, Zuzanna Staniszewska, Elizabeth H. Follmer, Muriel Van Gompel, Eline Jammaers, Ivy Mai, Samantha Young, Frederike Scholz, Amber Kersten, Manon Krabbenborg, Luca Smeets, Marianne van Woerkom

Bibliographic record

VenueAcademy of Management Proceedings · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFace (sociological concept)Diversity (politics)Work (physics)Quality (philosophy)Human resourcesInclusion (mineral)Resource (disambiguation)

Abstract

fetched live from OpenAlex

Neurodivergent employees bring unique talents that make them valuable to many organizations. However, they also encounter distinct difficulties in the workplace related to perceived misfit for tasks, how their skills are used and evaluated, and the quality of their social interactions. Although scholars have increasingly called for more research on the work experiences of neurodivergent employees, this aspect of diversity remains relatively underexplored, making it challenging for academics and practitioners to identify actionable strategies that promote the inclusion of neurodivergent talent in the workplace. This symposium addresses this gap by bringing together leading scholars who will shed light on how neurodivergent employees experience their work, the strategies they employ to overcome challenges they face and how this influences their careers, their attitudes and their wellbeing. Using the presentations as a starting point, the symposium aims to discuss common patterns, but also interesting differences in how neurodivergent employees navigate the workplace and the support organizations can offer to enable them to thrive. Furthermore, all authors included in this symposium have made a concerted effort to use the neurodiversity lens to advance theory in organizational behavior and human resource management. Perceived Misfit in the Workplace: A Qualitative Study of Autistic and ADHD Employees Author: Joanna Szulc; Gdansk University of Technology Author: Zuzanna Staniszewska; Kozminski University in Warsaw Author: Elizabeth Follmer; University of Washington A Conceptual Model for Neuro-Masking at Work Author: Muriel Van Gompel; Author: Eline Jammaers; Hasselt University Post Diagnostic Job Crafting Challenges and Opportunities for Employees with ADHD Author: Thomas Blondel; ESCP-Europe Business School - Berlin Author: Daniela Lup; ESCP Business School Author: Kerstin Alfes; ESCP Business School Navigating ADHD in the Workplace: Proactive Work Behaviours in Employees with ADHD Author: Ivy Mai; University of Calgary Author: Samantha Young; University of Calgary Creating a neurodivergent safe space in organizations Author: Frederike Scholz; Author: Amber Kersten; Tilburg University Author: Manon Krabbenborg; Author: Luca Smeets; Author: Marianne Van Woerkom; Tilburg University

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.086
GPT teacher head0.328
Teacher spread0.242 · 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
Published2025
Admission routes2
Has abstractyes

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