Management Research on Multinational Corporations: A Methodological Critique
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the context of burgeoning research on multinational corporations (MNCs), this paper\naddresses the issue of the representativeness of databases of MNCs in Ireland. It identifies some important deficiencies in existing databases much used by scholars in the field. Drawing on the international literature, it finds that this problem also characterises research on MNCs in many other countries. In the Irish context, we find that the extant empirical research has generally excluded two key categories of MNCs, namely, (a) foreign MNCs which are not grant-aided by the main industrial promotions agencies and (b) Irish-owned MNCs. The paper outlines our experience in identifying and addressing these deficiencies and describes the methods that might be employed in more precisely defining the MNC population in Ireland. More generally the paper reviews some of the issues and obstacles confronting scholars investigating the MNC sector in Ireland and abroad.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it