Strategic HRM Outside of Corporate HQ: Lost in Translation?
Bibliographic record
Abstract
The paper evaluates the importance of successfully transferring knowledge about Human Resources role to subsidiaries within Multi-National Corporations. The author presents result of the research conducted on a group of MNC's Head Quarter HR directors and HR managers/specialist in foreign subsidiaries. The study shows an influence of transfer of knowledge about HR's role on the construction of HR's image within organisations and HRM devolvement.Artykuł ocenia znaczenie transferu wiedzy na temat roli zarządzania zasobami ludzkimi do filii zagranicznych w ramach międzynarodowych korporacji. Autorka prezentuje wyniki badań przeprowadzonych na grupie dyrektorów personalnych w centralach korporacji międzynarodowych oraz menedżerach i specjalistach ds. zarządzania zasobami ludzkimi w ich zagranicznych filiach. Studium pokazuje wpływ transferu wiedzy na temat roli zarządzania zasobami ludzkimi na wizerunek działu personalnego wewnątrz organizacji oraz rozwój zarządzania zasobami ludzkimi.
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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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.004 |
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".