Business and the Planetary History of International Environmental Governance in the 1970s
Bibliographic record
Abstract
The role of business and multinational corporations (MNCs) in early international environmental governance is not well understood. Typically, historians accord business growing influence after the 1992 Rio Earth Summit, coincident with the rise of a market-oriented sustainable development paradigm. In this article, we highlight the considerable involvement of self-styled business actors in the formative 1972 UN Conference on the Human Environment and subsequent establishment of the UN Environment Programme. Tracing the interconnected networks of British economist Barbara Ward, Italian industrialist Aurelio Peccei and Canadian oilman-turned-UNEP boss Maurice Strong, we identify business actors as key in the passage from ‘planetary’ to ‘global’ environmental rationales characteristic of environmental politics between the 1970s and 1990s. However, we also show that business was a sought-after (even if often ambiguous) partner in the 1970s’ moment of innovative ‘planetary’ environmental thinking and institution making. The contested status of MNCs in 1970s internationalism shaped this early business involvement in the history of environmental governance.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".