A Research Agenda for Global Stakeholder Strategy
Bibliographic record
Abstract
This purpose of this article is to provide a framework into which we can integrate global strategy with stakeholder theory. Our aim is to create the basis for a research agenda that deals specifically with issues that are unique to global strategy and to use this perspective to demonstrate the insights that may arise for core stakeholder theory through the pursuit of such an agenda. We argue that a global perspective implies not only the management of stakeholders in various locations across the globe, but also the management of the rising phenomenon of multinationals and other organizations as truly global stakeholders. We argue that global stakeholder management involves a range of issues that are not yet fully considered either in the field of global strategy or the field of stakeholder theory. For example, drawing on recent research that emphasizes stakeholder claims as arising from rules of law, global strategy can involve selectively exposing the corporation across jurisdictions to particular stakeholders. This presents an opportunity for gains from the trade in intellectual ideas, concepts, theories, and empirical findings.
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 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 | 0.038 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.015 | 0.035 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".