Rethinking the transfer of the organisational culture model as a process of change
Bibliographic record
Abstract
This study adopts a comprehensive approach of organisational culture, through the use of Schein's (2004) cultural model, to understand the complexities and nuances of the process of transferring both the most and the least visible aspects of culture from a multinational corporation (MNC) to its foreign subsidiaries. A single case study of a Mexican MNC is analysed through interviews with human resources executives and company documents. The findings show that the least visible aspects of organisational culture do shed light on the cultural model transfer and that the flexibility to change and/or adapt this model from headquarters (HQ) to the foreign subsidiaries is desirable to accomplish some level of cultural integration. MNCs need to involve managers and employees from HQ and foreign subsidiaries in the change and sense-making processes during the organisational culture transfer. Rigid attempts at imposing cultural mechanisms of control can increase the cost in terms of dealing with resistance.
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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 | 0.034 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.045 |
| Scholarly communication | 0.021 | 0.027 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| 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".