The UN’s Sustainable Development Goals: Can multinational enterprises lead the Decade of Action?
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
The Sustainable Development Goals (SDGs) were adopted in 2015 by all UN member states and have been embraced by many multinational enterprises (MNEs) and international NGOs. They created a ‘hybrid governance’ platform in which companies, governments, NGOs, and knowledge institutes can work on achieving common goals through targeted action and serve as the leading global sustainable development framework until 2030. By the year 2020, however, progress towards the goals proved slow, prompting the UN to announce a ‘Decade of Action’. The slow or limited adoption and implementation of the SDG Agenda by MNEs – in close interaction with government policies – is one of the root causes for delayed progress. The question is no longer ‘why’ MNEs should develop sustainability strategies, but rather ‘how’. A number of related questions arise. What have been the roles of MNEs in progress towards the SDGs, what is needed from them in the future, and what can be the role of international business (IB) scholarship in shaping discussion and action? This Special Issue tackles these questions from four angles: (1) identifying and helping to fill theoretical gaps in IB research on the SDGs; (2) asking which SDGs and targets provide promising venues for societally relevant IB research topics; (3) assessing and helping to fill empirical gaps by using, complementing, and upgrading relevant SDG indicators; and (4) showing how IB research and policy practice can become better aligned.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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