Sustainable Development, Evaluation and Policy-Making: Theory, Practise and Quality Assurance edited by Anneke von Raggamby and Frieder Rubik
Bibliographic record
Abstract
Appearing in the ‘Evaluating Sustainable Development’ book series, Sustainable Development, Evaluation and Policy-Making, Theory, Practise and Quality Assurance comprises 15 essays organised into five sections: 1), perceptions of sustainability and related issue s ; 2), evaluation and assessment in policy formulation; 3), policy implementation in different areas; 4), policy reformulation and monitoring; and finally 5), quality of evaluations. A general introduction written by the co-editors plus Anna Hirschbeck, preceds these essays, provides a few definitions, and explains how the contributions in each section hold together. Interestingly, about half of the contributors come from Germany and the Netherlands. Thus, many of the references and policies studied here are from these countries, which will be inspiring and perhaps thought-provoking for many American readers. This is one of the strengths of this collection of essays: we are granted these specific perspectives and varied European contexts. The contributions by German scholars in this book are particularly important and instructive, for at least two reasons. First, they are strongly grounded in theory; and secondly, they rely on sources and frameworks in the German language that are not always familiar to Anglophone readers. All contributors provide definitions, case studies, data, useful figures, comparisons, and theoretical thoughts, sometimes already familiar, and in other cases innovative (p. xiii). For instance, the first objective of social-ecological research quoted in the (too short) Introduction seems to be derived from the definition of sustainable development carried in the famous Brundtland Report from 1987, which promoted: … the ecological modernisation of society without neglecting mankind’s desire for social justice and prosperity. (p. xiv) … development that meets the needs of the present without compromising the ability of future generations to meet their own needs. (p. 44) … a common definition of sustainability does not currently exist. (p. 210) … for sustainability evaluations to equally address all dimensions of sustainable development. (p. xiii) … fostering cross-disciplinary pooling of knowledge to provide scientific contributions to solving concrete social problems of sustainability and requiring interdisciplinary cooperation between researchers in the natural and the social sciences. (p. xiv) … encouraging research to look beyond the science system and take into account the expert knowledge which exists in practice by including social actors such as consumers, municipalities, companies and civil society in the research process in different ways (transdisciplinary). (p. xiv)
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.035 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".