Disability Severity, Professional Isolation Perceptions, and Career Outcomes: When Does Leader–Member Exchange Quality Matter?
Bibliographic record
Abstract
Employees with disability-related communication impairment often experience isolation from professional connections that can negatively affect their careers. Management research suggests that having lower quality leader relationships can be an obstacle to the development of professional connections for employees with disabilities. However, in this paper we suggest that lower quality leader–member exchange (LMX) relationships may not be a uniform hurdle for the professional isolation of employees with disability-related communication impairment. Drawing on psychological disengagement theory, we predict that employees with more severe, rather than less severe, communication impairment develop resilience to challenges in lower quality LMX relationships by psychologically disengaging from professional connections and, in turn, bear fewer negative consequences of professional isolation on career outcomes. In two studies of deaf and hard of hearing employees, we find that in lower quality LMX relationships employees with more severe communication impairment perceive being less isolated than employees with less severe communication impairment, and, in turn, report better career outcomes. Overall, our findings suggest that employees with more severe communication impairment may develop effective coping strategies to manage challenges of perceived professional isolation for career outcomes when in lower quality LMX relationships.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".