From "for" to governance for sustainable development in Europe: what is at stake for further research?
Bibliographic record
Abstract
Following conferences in Pignans, Maastricht, Vienna and Cologne and many e-mail exchanges, the participants of the GoSD-research initiative have identified a path for future research that describes not only governance and sustainable development but also how governance can be *for* sustainable development. This concluding paper gives an account of the pre-analytic vision, hypotheses and questions that have so far emerged from this process. Given the difficulty and importance of the task, a first section focuses on methodological questions. Consecutive sections elucidate *for sustainable development*, as well as "governance for". The emerging pre-analytic vision then receives some in-depth treatment and we consider how to measure the *for* of governance for sustainable development through objectives and indicators, taking into account the paradox of change with conservation. This sets the stage for a final section on research hypothesis and questions that give a meaning to governance for sustainable development, and that will allow this research project to develop in a way that makes insight and useful policy recommendations possible.
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 | 0.031 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.022 | 0.025 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".