Bibliographic record
Abstract
The retention of existing IT employees is crucial due to the expected shortage of the IT labor force in the U.S., Canada, and European countries. While much of the extant IT turnover literature implicitly assumes that IT employees are homogeneous, we contend that they are a diverse group and that exploring the group in depth would reveal further insights into why employees turnover. We examined a sample of employees by IT job type in a turnover model of the antecedents and impacts of perceived organizational support (POS), which is another infrequently studied concept in the literature but is a potentially important predictor of turnover. A survey of 302 IT employees at a large U.S.-based company showed that these employees are in fact diverse. The relationships between role ambiguity and POS and work schedule flexibility and POS were found to be significant for managerial employees, but not for technically-oriented employees. The relationship between career accommodations and POS, however, was found to be significant for technically-oriented employees, but not managerial employees. As a whole, this study suggests that by combining all IT employees together in our analyses, we may forego some of the unique insights about these employees that we can otherwise cultivate to strengthen the bond between the organization and its employees and to enhance our existing IT turnover literature. The results of this study provide implications for organizations on how they can better balance the tactics they use to retain their valued IT employees. IT managers can be in a better position to focus on building relationships with their employees based on what is generally important to those employees.
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 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 | 0.001 | 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 | 0.011 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".