What if the Dream World of Business Already Existed?
Bibliographic record
Abstract
In September 2015 the UN Global Compact presented the most ambitious agenda for a world as we would like it: the 17 Sustainable Development Goals (SDGs). They were the first initiative approved by all the 193 member states. The implications of this global agenda differ from the previous Millennium Development Goals, which were seen as a responsibility of the governments, not of civil society or corporations. This time, in addition to a political or administrative task of government, the call is for investors and asset management institutions, for business and for educational institutions, via PRME (Principles for Responsible Management Education), and accreditation organisms (AACSB, EQUUS). To give an example, hosted by a number of industrial and financial corporations (Citi, SABMiller, Mars, GlaxoSmithKline and others) in September 2016, an international event called Business Fights Poverty brought together 130 representatives from business, government and civil society to discuss how business can collaborate more effectively to deliver the SDGs. The interface of education, business and SDGs is developing as a powerful constellation that can accelerate change. According to Jane Nelson, Director of the Corporate Responsibility Initiative at Harvard Kennedy School, the estimated investment needed to reach the SDGs is between $3 to 6 trillion, which will need to come from business and government alike. This means that at the local level new capabilities will have to be developed, through education and training. All is pointing at a new business model, that can unite profit with products or services that address real global needs, now framed under the SDG agenda. In this Panel Symposium a group of international professors will share their experience as they introduced the SDGs and a different economic model to their students, and the impact it had on their audience. Professors from India, Russia, Indonesia, Philippines, Nigeria, Canada and the US will bring thought provoking stories to the session and engage in a dialogue with the audience.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.029 |
| Scholarly communication | 0.039 | 0.060 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.011 | 0.017 |
| Insufficient payload (model declined to judge) | 0.022 | 0.011 |
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".