The roles of multinational enterprises in implementing the United Nations Sustainable Development Goals at the local level
Bibliographic record
Abstract
Multinational enterprises (MNEs) play a fundamental role in advancing the implementation of the United Nations Sustainable Development Goals (SGDs), as they enable cities and communities to reach large-scale solutions. In this article, we analyze 348 MNEs’ sustainability reports with explicit reference to the SDGs to identify the different roles that MNEs play in advancing the SDGs at the local level. Through qualitative content analysis, the literature on MNEs’ roles was validated, extended, and two new roles were found. The five roles of MNEs in local sustainable development that were validated are financer, community capacity builder, product and service provider, partner, and innovator. The three that were extended are employee developer, supply chains and procurement developer, and program deliver, while the two new additions are consultant and awareness raiser. The results of bivariate analyses show that some MNE roles are correlated to headquarter region and the industry sector. The 10 roles are also relevant for implementing all 17 SDGs and 102 of the 169 SDG targets. JEL CLASSIFICATION: M14
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".