<scp>IASSIDD A</scp>cademy on <scp>E</scp>ducation, <scp>T</scp>eaching, and <scp>R</scp>esearch: The Genesis and Evolution of an Idea
Bibliographic record
Abstract
Abstract The author provides an overview of the development of the IASSIDD Academy from its inception to December 2013. The commentary represents the personal reflections of the founding director of the Academy in terms of its mission and its history of carrying out activities around the world. Outlined are some of the challenges and successes, as well as some of the future needs in terms of the Academy's relevance both inside and beyond IASSIDD. The author notes that with the formation of a board of directors, the development of IASSIDD Academy bylaws along with mission statements, and the design and work with various agencies and communities around the world, the Academy has now moved into a period of consolidation and renewed progress.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".