Bibliographic record
Abstract
Purpose This study addresses the perspective of N = 273 school principals as related to technology role in performing managerial roles. Design/methodology/approach In the context of this study, the concept of technology only refers to digital office tools such as microcomputers, email and administrative software. The concept of managerial roles is understood and used herein in relation to the definition provided by Mintzberg (2013) in his managerial typology. Moreover, a survey method was used to collect data from the aforementioned managerial employees. The managerial typology of Mintzberg was applied as a theoretical lens to collect and interpret survey data. Findings The findings suggest that surveyed school principals believe that technology use improves their ability to perform informational and decisional roles at work. Arguably, these managerial employees are satisfied with using technology as a labor tool for administrative and managerial work. Research limitations/implications This study is limited because its sample size does not allow the findings to be generalized to all Canadian school principals. Nevertheless, the findings are significant because they suggest that similar to the positive technology-related attitude of managerial employees in business organizations, those in school organizations also perceive technology as an organizational asset. For that reason, management scholars should not only limit their studies of the intersection between technology and managerial roles or work to business organizations. They also need to extend their research studies and fieldwork to school organizations. Originality/value The originality of this study lies in the fact that in management literature, the intersection between technology and the managerial roles of school principals is underresearched. As such, this study represents a step forward toward the need to study the technology-related behaviors of school principals to better understand how technology use enables their workflow system.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".