Multinationals’ Compliance with Employment Law: An Empirical Assessment Using Administrative Data from Ontario, 2004 to 2015
Bibliographic record
Abstract
This study contributes new evidence to the literature on multinational corporation (MNC) behavior by exploring three related questions: 1) Do MNCs comply with local employment laws in a developed country? 2) To the extent that compliance varies across MNCs, what factors are important in shaping compliance? 3) Is there a “foreignness” effect for MNCs operating in developed countries, and does this effect vary according to country-of-origin and/or union status? To investigate these questions, the authors compiled unique firm-level administrative data on MNC compliance with regulatory and quasi-regulatory employment practices during mass layoffs in Ontario, Canada. Adopting a research design that uses the behavior of Canadian MNCs as the comparison group, their key findings suggest that unions are a very robust predictor of compliance across all foreign MNCs and systematic country-of-origin effects on MNC compliance are present only in non-unionized workplaces.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".