Bibliographic record
Abstract
Maurice StrongWe live in paradoxical times.At a time when our society is experiencing an information revolution, systemic gaps have developed in how we communicate with one another.These gaps in the timely transfer of knowledge between the academic, industrial, government, and nongovernment solitudes seriously affect our progress as a nation into the twenty-first century.Yet to move forward in any field requires knowledge about the issues at hand and demands that all stakeholders have a common understanding of the information, that gaps be identified and bridged, and that barriers to action be removed.In order to make a difference, this information must be relevant, timely, accurate, and noticed.Gaps in our knowledge affect our capacity as a nation to respond to international obligations arising from the United Nations Conference on Environment and Development -the Earth Summit -and our commitments to Agenda 21.It is important that these gaps be corrected in order for us to contribute in a meaningful way to public policy decisions and actions leading to sustainable development.Accomplishing this goal will require extensive cooperation, information exchange, and knowledge sharing among all sectors of Canadian society.In order to meet this need, the Sustainable Development Research Institute of the University of British Columbia plans to publish books in a sustainable development series.Our intention is to stimulate an exchange of information between academic communities, governments, non-government organizations, and industry.We hope to go far beyond simply presenting information by producing policy analysis and specific recommendations in each book.The series will provide comprehensive, independent, and critical discussion about the actions required of various sectors of society and individual Canadians to meet
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.657 | 0.602 |
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".