UNITED NATIONS ECONOMIC COMMISSION FOR EUROPE MEASURING SUSTAINABLE DEVELOPMENT Prepared in cooperation with the Organisation for Economic Co-operation and Development and the Statistical Office of the European Communities (Eurostat)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The designations used and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Acknowledgements This publication is the result of the fruitful two years of productive cooperation of the members of the Joint UNECE/OECD/Eurostat Working Group on Statistics for Sustainable Development and its Steering Committee, chaired by Robert Smith from Statistics Canada. The work has benefited from the valuable contributions by the members of the Working Group who actively participated in the meetings. During the course of the work, many members of the Working Group and its Steering Committee have contributed papers as an input to the discussions. The list of authors who contributed papers is presented in the Bibliography of this publication. The Bureau of the Conference of European Statisticians has provided constructive guidance and assistance to the Working Group throughout the work. The UNECE provided secretariat support to the Working Group. The OECD and Eurostat also supported the work. Statistics Norway and the Norwegian Ministry of Finance have given financial support to research papers and to the Editor of the report.
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.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it