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The Power of a Proper Propper: Formal and Informal Organizational Support for Neurodiversity

2025· article· en· W4416000185 on OpenAlexaff
Nikki Drader-Mazza, Joshua J. Prasad, Samantha Hancock, Jennifer A. Griffith, Tracy Powell-Rudy, Annika L. Benson, Colin Willis, Elizabeth H. Follmer, Judy Reilly, Stephen DeStefani, Andrew Millin, Katie Badura, Debra R. Comer, Jennifer L. Schultz

Bibliographic record

VenueAcademy of Management Proceedings · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsWestern University
Fundersnot available
KeywordsState (computer science)Power (physics)Representation (politics)Formal educationEmpirical research

Abstract

fetched live from OpenAlex

Modern organizations are increasingly recognizing the benefits of employing neurodivergent workers. As the representation of neurominorities in the workplace continues to rise, management scholars and practitioners alike are interested in examining how best to support this historically underrepresented subset of the workforce. In this symposium, researchers collaborate with industry-leading practitioners to investigate formal and informal support practices that promote the inclusive employment of individuals who identify as neurodivergent. Drawing on both conceptual and empirical research, we explore the theoretical and practical implications of both formal and informal forms of support for neurodivergent employees, their supervisors, and the organization as a whole. The papers presented in this symposium emphasize that unlocking the potential of neurodivergent and neurotypical employees alike is fostered through both informal support practices and the formal support practices upon which they are built. Toward a Theory of Workplace Accommodations for Autistic and ADHD Employees Author: Joshua Prasad; Colorado State University Author: Samantha Hancock; Western University Author: Kartik Trivedi; Author: Jennifer Griffith; University of New Hampshire Author: Annika Benson; Colorado State University Author: Tracy Powell-Rudy; Author: Justine Chalifour; - Author: Colin Willis; - I Can Speak Clearly Now the Training’s Done: Spillover Effects of Neurodiversity Training Author: Elizabeth Follmer; University of Washington Author: Nikki Drader-Mazza; University of North Texas Author: Judy Reilly; Author: Stephen DeStefani; - You Get What You Give: Spillover Effects of Managing Neurodivergent Employees Author: Nikki Drader-Mazza; University of North Texas Author: Andrew Millin; Florida International University Author: Katie Badura; Georgia Institute of Technology Author: Virginie Lopez Kidwell; University of North Texas Author: Judy Reilly; Author: Stephen DeStefani; - You Just Might Find, You Get What You Need: Neurodivergent Academics’ Reliance on Informal Support Author: Debra R. Comer; Hofstra University Author: Jennifer Lynn Schultz; Minnesota State University Mankato Author: Elizabeth Follmer; University of Washington

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.328

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 studies0.0000.000
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 head0.019
GPT teacher head0.295
Teacher spread0.276 · 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 routes1
Has abstractyes

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