Rethinking contexts and institutions for research on human resource management in multinational enterprises in an age of polycrisis: reflections and suggestions
Bibliographic record
Abstract
International human resource management (IHRM) has covered two very distinct areas: comparative HRM (comparing HRM between national settings) and HRM in multinational enterprises (MNEs). Existing research has pointed to the multifaceted nature of contextual effects, and how they may differ qualitatively according to locale. This perspective article argues that a distinct and shared theme across this literature is much more than a recognition that many different sets of institutions and/or cultural features can make for viable alternative HRM models. We also consider whether or not MNEs seek to accommodate local realities or work to change them. Developing and broadening inquiry around these concerns may represent a solid way for researching IHRM in an age of polycrisis. Such understandings may be of great value in exploring the relationship between the present global polycrisis and HRM practice. We highlight potential concerns and opportunities for theorizing around the same.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".