Assessing the Generalizability of Managerial Discretion: An Empirical Investigation in the Arab World
Bibliographic record
Abstract
The purpose of this paper is to examine the generalizability of national-level managerial discretion and to assess whether the national context play a role in changing mainstream research findings. Based on a sample of three Arabian countries and using a panel of prominent cross-cultural scholars who provided 138 discretion scores for the sampled countries, we replicate the national framework of Crossland and Hambrick (2011) in a new cultural context. The cultural dimensions were measured via survey responses of 375 middle-managers based on House et al. (2004) cultural practices scale. Consistent with Crossland and Hambrick (2011), we demonstrate that individualism and uncertainty tolerance have the same positive effect on CEOs discretion even in a different cultural setting. In contrast, we show that power distance has a positive and significant effect on managerial discretion. Our results indicate that executives can take idiosyncratic and bold actions to the extent to which the cultural environment allows them to do so. Accordingly, we contribute by showing the importance of the national setting in affecting the generalizability of discretion findings.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".