Work intensity: potential antecedents and consequences
Bibliographic record
Abstract
Purpose - The purpose of this exploratory research is to examine the relationship of a measure of work intensity with potential antecedents and consequences. Design/methodology/approach - A questionnaire was developed and pre-tested. It included a new 15-item measure of work intensity. Data were collected from 106 respondents enrolled in three university business courses using anonymously completed questionnaires. Regression and factor analyses were used in developing the measure and testing the relationships. Findings - The 15-item measure of work intensity was found to have high internal consistency and reliability. Work intensity was significantly related to respondents' organizational level and work status. In addition, respondents indicating higher levels of work intensity also reported working more hours, a higher workload, and greater job stress. Work intensity was unrelated to organizational values supporting work-personal life imbalance, three workaholism components, or to indicators of work engagement. Factor analysis of the work intensity measure produced three factors: emotional demands, job demands, and time demands, the first two were fairly consistently related to other study variables, whereas time demands was not. Research limitations/implications - The sample was relatively small and the data were collected using self-reports. The design was cross-sectional, thus limiting causal inferences. Practical implications - Managers will find the study useful in assessing the effects of work intensity and working long hours for employees, including stress levels and work engagement. Originality/value - The study developed a work intensity measure and examined its properties and correlates, something that is lacking in the literature.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".