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Neurodiversity in Organizations: Beyond the Basic Accommodation Model

2023· article· en· W4385224803 on OpenAlexaff
Chloe R. Cameron, Robert D. Austin, Tiffany Dawn Johnson, Jennifer R. Spoor, Christine Nittrouer, Mirit K. Grabarski, Nancy Doyle

Bibliographic record

VenueAcademy of Management Proceedings · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Learning and Leadership
Canadian institutionsLakehead University
Fundersnot available
KeywordsAccommodationPsychologyCognitive scienceSociologyEpistemologyPhilosophyNeuroscience

Abstract

fetched live from OpenAlex

Neurodiversity inclusion is no longer a new topic in business, yet it continues to be understudied at macro, meso, and micro levels of the organization. This symposium consists of five short presentations, each investigating a different aspect of neurodiversity in organizations across these levels. Nittrouer, Blake, and Lux start at the macro level, looking at the relationship between DEI statements (as they relate to neurodiversity and multiculturalism), five organizational outcomes/traits, and the marginalized identities of DEI officers. Next, Cameron and Austin discuss the cross-level impact of diversity, employee support systems, and structured conflict management systems on the intragroup conflict process in organizations by drawing on data from neurodiversity employment initiatives. Third, Doyle investigates the cross-level impact of coaching on dimensions of executive functioning and self-efficacy in neurominority participants in the context of reasonable accommodations at work. Fourth, Grabarski and Baker present a primarily micro-level study on how perceptions of neurodiversity inclusion impact individuals in terms of affective commitment and turnover intention. Finally, Spoor and Jameson overview the implications of neuro-inclusion for business schools and discuss practical implications for teaching, research, and administration across the business school as a call to action. A group discussion will be led by Johnson, touching on research comments, theoretical and practical implications. DE&I Officers and DE&I Statements Author: Christine Nittrouer; Texas Tech U. Author: Sean Lux; Texas Tech U. Author: Andrew Blake; Texas Tech U. Organizational Emotional Intelligence in Diversity Management Author: Chloe R. Cameron; Ivey Business School Author: Robert Austin; Ivey Business School Coaching as an Accommodation for Neurodivergent Employees Author: Nancy Doyle; Birkbeck U. of London Exploration of Neurodiversity Perceptions in Australian Retail Author: Mirit K. Grabarski; Lakehead U. Author: Marzena Baker; U. Of Sydney Supporting Neurodiversity in Organizations: The Role of Business Schools Author: Jennifer R. Spoor; La Trobe U. Author: Tiffany Payton Jameson; -

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.030
GPT teacher head0.231
Teacher spread0.200 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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