Looking for a ‘just transition’: Sustainable forestry in Sweden and biodiverse beet sugar production in Denmark
Bibliographic record
Abstract
This article aims to identify contradictions between visions of just transition and their realisation in practice, particularly the extent to which labour and nature are respected, with examples of forestry in Sweden and the beet sugar industry in Denmark. The case studies provide insight into the formation and local implementations of the just transition vision promoted by the ITUC and ILO, representing a call for the ecological modernisation of the economy. The cases illustrate its Northern European roots and limitations. Although a multi-scalar perspective positions union agency as embedded in interwoven spatial scales, particular power relations remain prevalent. Despite being formally represented through social dialogue structures at the national and European levels, Swedish and Danish unions appear to have limited involvement at the local level, with environmental and social justice effectively defined by corporate social responsibility policies. The apparent consensus hides a series of challenges: employment rights and protections in the transition, including for a significant number of migrant workers, meaningful union involvement on the ground, and a light-touch approach to environmental concerns so as not to disrupt production objectives. Ultimately, nature and labour remain positioned against each other, and unions are caught between environmentalists and employers.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".