The Inter Business Index Developing a Tool for Measurement and Comparability of Holistic Sustainability in Businesses
Bibliographic record
Abstract
The scope of sustainable development is undoubtedly growing, and becoming increasingly more important due to the process of globalization, amounting in complex environmental, societal and economic issues. Although the subject of business sustainability has been gaining traction and resulted in increased knowledge in the field, the business sustainability discourse is still at a young stage, where the different streams of approaches, definitions, systems and measures are fragmented and challenged. Today’s global challenges are so large and complex that they require a new kind of problem-solving and way of doing business. Identifying solutions requires a diversity of perspectives, approaches and capabilities, and the business sector plays a critical role. The integrated approach has been examined to some extent, proposing a holistic manner of moving on to true business sustainability, and a sustainable development on a global scale. This article presents the concept of Inter Business and the Inter Business Index, a tool for measurement and comparability of holistic sustainability in businesses. The Inter Business framework consists of four key-components that describe the skills needed for future-preparedness. In our research, we have analysed the 50 biggest corporations in Sweden and identified purpose, empathy, system approach and transformation as components that respond to the hypothesis that interconnection and integration are key for companies to survive and thrive, whilst contributing to society at large.
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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 | 0.041 | 0.144 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.021 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".