The AAAS 2012 Annual Meeting: flattening the world: building a global knowledge society
Bibliographic record
Abstract
Purpose The purpose of this paper is to report on six Symposia offered at the 2012 Annual Meeting of the American Association for the Advancement of Science (AAAS), held 16‐20 February 2012, in Vancouver, Canada. The theme of this 178th Meeting was: “Flattening the world: building a global knowledge society.” Design/methodology/approach This report includes summaries of the salient points in each panelist's presentation for the selected Symposia, and it provides internet links to further support the content of the presenters' comments. Findings The AAAS 2012 Annual Meeting aimed at exploring a broad range of recent discoveries and looming global challenges. The program focused on the current complex, interconnected challenges of the twenty‐first century and on pathways to global solutions through international, multidisciplinary efforts. Originality/value This report provides insights on the current research themes such as interdisciplinary collaboration, community‐engaged scholarship, global outreach by sharing science and research data with the public, building collaboratories for research on a global scale, and reducing international knowledge isolation of the “Global South” (the nations of Africa, Central and Latin America, and most of Asia).
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.023 | 0.009 |
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".