The effects of linguistic ostracism on job performance: A replication and an extension
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We examined the phenomenon of linguistic ostracism—instances where a focal workgroup member perceives other members of their workgroup have rejected and/or excluded them by using a language they cannot comprehend. In a 2021 article, Fiset and Bhave observed that linguistic ostracism was related to two dimensions of job performance (interpersonal citizenship and deviance) and that disidentification served as an explanatory mechanism for the linguistic ostracism–job performance relationship. We constructively replicate and extend their work in several ways. First, we replicate prior effects on interpersonal citizenship and deviance and extend their work to focus on a third dimension of job performance: task performance. Across two studies, we find that linguistic ostracism was associated with lower task performance. Second, we identify an additional mechanism for the linguistic ostracism–job performance relationship: belongingness need satisfaction. Third, we observe that sinister attributional tendencies moderated the indirect effect of linguistic ostracism on performance via belongingness need satisfaction and disidentification. The pattern of this moderated-mediation effect indicated that employees with high (vs. low) sinister attributional tendencies tend to exhibit decreased performance. Our findings thus offer three extensions to Fiset and Bhave’s work and highlight the need for organizations to recognize linguistic ostracism and proactively manage language diversity at work.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it