The Relationship between Architects’ Quality of Work Life and Their Productivity: A Case Study
Why this work is in the frame
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Bibliographic record
Abstract
The goal of quality of work life is to evaluate how employees perceive their lives inside a company. Lack of quality of work life is linked to greater levels of occupational stress, anxiety, and burnout, leading to poorer job performance and substantial expenses for organizations. Bearing this in mind, the current study was formulated to address the gap in the literature and examine the relationship between architects’ Quality of Work Life and their productivity throughout a case study in Kerman, eastern Iran. To fulfil the objectives of this study, 130 architects working actively and officially in Kerman agreed to participate in the study, who were reached out using the Krejcie, and Morgan’s (1970) table. Two questionnaires in Persian Version were distributed among them, including Quality of work life questionnaire based on Walton model (1973) and the Productivity questionnaire based on the ACHIEVE model, both adopted from Chalabiei (2017). The data was transferred to SPSS Version 27 for further statistical analyses. The results of the Spearman's correlation coefficient test showed that there was a positive correlation between the quality of work life and the architects’ productivity. Also, all the eight components of quality of work life had a positive relationship with the architects’ productivity. Further implications of the study results and suggestions are discussed, accordingly.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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