THE COMPLEXITY OF RESPECTING TOGETHER: From the point of view of one participant of the 2012 Vancouver NAACI conference
Bibliographic record
Abstract
Dedication: I would like to dedicate this essay to Mort Morehouse, whose intelligence, warmth, and good humour sustains NAACI to this day. I would like, too, to dedicate this essay to Nadia Kennedy who, in her paper “Respecting the Complexity of CI,” suggests that respect for the rich non-reductive emergent memories and understandings that evolve out of participating in the sort of complex communicative interactions that we experienced at the 2012 NAACI conference requires “a turning around and looking back so that we might understand it better.” Thus, though “we cannot grasp the essence of the system in some determinate way, since each description provides a limited view, and portrays some aspect of the system from a specific position inside or outside it, and at a specific point in time,” nonetheless respect requires that we try “to take different ‘snapshots’ of such systems and attempt to make sense of them.” It is as a result of this urging that the following snapshot was attempted. My thanks to Nadia for being such an inspiration, and to all the participants for making this conference such a memorable occasion.
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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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.074 | 0.047 |
| Scholarly communication | 0.035 | 0.012 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.009 | 0.033 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".