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Record W4387369940 · doi:10.1108/omj-03-2023-1810

Hidden challenges: an invisible disabilities learning activity

2023· article· en· W4387369940 on OpenAlexaff
Nicole Bérubé

Bibliographic record

VenueOrganization Management Journal · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsRoyal Military College of CanadaQueen's University
Fundersnot available
KeywordsDebriefingExperiential learningLearning disabilityOriginalityPsychologyValue (mathematics)Equity (law)Medical educationSocial psychologyPedagogyComputer scienceMedicineDevelopmental psychology

Abstract

fetched live from OpenAlex

Purpose This paper aims to describe an experiential learning activity designed to sensitize students to the prevalence and challenges of disclosing invisible disabilities in the workplace. It provides an impactful learning experience about a widespread phenomenon that receives little attention in textbooks. Design/methodology/approach The exercise assigns a hidden disability to some participants who interact with others who act as trusted friends. The interactions help participants develop their ability to interact sensitively with those who may have hidden disabilities. They explore the advantages and disadvantages of disclosing hidden disabilities at work. Guiding questions help focus deliberations during which participants consider the influence of their assigned role. Findings A plenary discussion follows where students share the outcomes of the simulation. Debriefing questions and suggested answers help instructors deepen student learning on the topic. A follow-up assignment allows participants to summarize personal learning about the subject and solidify the learning outcomes. Originality/value Most workers with nonapparent disabilities hide them, although disclosing them may help their employers provide helpful accommodations. This learning activity helps increase awareness and understanding of hidden disabilities in work settings and supports learning about disclosing and accommodating disabilities in the workplace. Instructors can use the activity to support understanding of employee rights, equity and accommodations in large or small classes, in-person or online, synchronously or asynchronously.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.069
GPT teacher head0.345
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.

Study designQualitative
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

Citations5
Published2023
Admission routes1
Has abstractyes

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