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Record W2150839433 · doi:10.7202/016487ar

Impediments to Disability Accommodation

2007· article· en· W2150839433 on OpenAlexaffvenue
Kelly Williams‐Whitt

Bibliographic record

VenueRelations industrielles · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsAccommodationAffect (linguistics)CredibilityLegitimacyReasonable accommodationGrounded theoryPublic relationsConfidentialityNormativeWorkloadPsychologyQualitative researchSocial psychologyBusinessPolitical scienceSociologyLawManagement

Abstract

fetched live from OpenAlex

The results of a qualitative field investigation exploring how tripartite relationships affect disability accommodations are reported. Arbitration cases, in-depth interviews and other documentation are analyzed using grounded theory techniques. Four key categories emerge as contributors to difficult accommodations. The first category suggests that managerial reluctance and bias may stem from added workload or from questions about disability credibility. It further demonstrates how trust issues spill over to affect future accommodations. The second category, employee involvement, indicates that excluding the disabled employee from accommodation planning occurs frequently and has a negative affect on communication patterns, again damaging trust. The third category, ineffective investigation, highlights the difficulty managers have balancing confidentiality requirements: over-investigating illness legitimacy and under-investigating accommodation options. The final category, union-management climate, looks at union roles in accommodation and suggests that while unions often play a unique and positive role, substantial union-management animosity taints return-to-work efforts.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.043
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.006
Scholarly communication0.0040.003
Open science0.0010.013
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.058
GPT teacher head0.379
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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

Citations30
Published2007
Admission routes2
Has abstractyes

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