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
This article explores the role of multinational enterprises (MNEs) in sustainable development by drawing on the perspectives of four distinguished management scholars—Stuart Hart, Ans Kolk, Sanjay Sharma, and Sandra Waddock—as well as the extant literature on sustainability, corporate social responsibility, and international management. The discussions are centered around “Sustainable Global Enterprise” (SGE)—a new concept coined by Hart. Hart labels those MNEs that can generate competitive strategies that simultaneously deliver economic, social, and environmental benefits for the entire world as SGEs. Through deliberations with the above leading thinkers, this article offers insights into how MNEs can imbue the sustainability principles into their strategic framework and simultaneously contribute to sustainable development. The article also sheds light on the enormous new research opportunities yet to be tapped by international management and sustainability scholars.
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.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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