Feeling possessive, performing well? Effects of job-based psychological ownership on territoriality, information exchange, and job performance.
Bibliographic record
Abstract
Job-based psychological ownership arises when workers develop personal feelings of possession over various aspects of a job. Drawing on conservation of resources and regulatory focus theory, the current research adopts a resource-based perspective to suggest a double-edged effect on job performance, mediated by three forms of territoriality (marking, defending, expanding) and information exchange and moderated by individual regulatory focus. With a multistep process in Study 1, the authors develop and validate a territorial expanding scale. Among 358 employee-supervisor dyads, Study 2 tests the proposed model; job-based psychological ownership prompts employees to engage in territorial marking, defending, and expanding. Territorial defending correlates negatively with information exchange, territorial expanding is positively related to it, and territorial marking has no relationship with information exchange. Information exchange is positively related to job performance. Job-based psychological ownership impedes job performance through increased territorial defending and reduced information exchange, especially among employees with a prevention focus. It enhances job performance through increased territorial expanding and increased information exchange, particularly if employees have a high promotion focus. These findings have notable implications for research and practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
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".