Onko talouskasvun ja ympäristöpaineiden irtikytkennässä onnistuttu? Tapaus Suomi
Bibliographic record
Abstract
We look at decoupling environmental pressures from economic growth first at a conceptual level and then empirically, focusing on Finland. First, we distinguish between different types of decoupling, analysing easier and more difficult forms. The absolute, long-term and sufficiently rapid economy-wide decoupling required for ecological sustainability is more challenging than the cases of decoupling a single pollutant or a single economic sector presented in the literature. Since different forms of decoupling are not necessarily (logically, materially) related, special care must be taken when presenting decoupling as a solution. In the empirical section, we consider, first, the decoupling of GDP from resource consumption, and second, the decoupling of GDP from greenhouse gas emissions. In terms of resource consumption, a decoupling possibly consistent with ecological sustainability would require that in 2050 the materials used would create 6.6 times more monetary value than in 2022, while the total material use would be about a quarter of what it is today. Similarly, for greenhouse gas emissions, successful decoupling would require a tripling of the current decoupling rate of net emissions. These results pose a serious challenge to economic and environmental policy approaches relying on the idea of decoupling.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.006 |
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".