Bibliographic record
Abstract
Abstract Work attitudes are evaluations of an employee's job and work environment. Job satisfaction and organizational commitment are two of the most globally studied work attitudes. Antecedents and consequences of work attitudes vary across cultural contexts. For example, extrinsic job characteristics such as job security and pay are positively related to job satisfaction across collectivistic cultures, whereas intrinsic job characteristics such as recognition and autonomy are more strongly related to job satisfaction in individualistic countries. Consequences of work attitudes also vary across cultures. Normative commitment has been found to be a better predictor of job outcomes in collectivist contexts because of the strong emphasis on social ties and obligations whereas affective commitment is a more powerful predictor of job outcomes in North America. Other than culture, socioeconomic factors also affect employees' work attitudes. In developed countries individuals have the possibility to choose between different types of organizations and the type of the work they would like to do and as a result they would experience higher job satisfaction. On the other hand, in less developed countries continuance commitment would be observed because of the fewer choices individuals have and their obligation to do jobs that are not so satisfying for them.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.152 | 0.044 |
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".