CHAPTER ONE A UNIQUE INSTITUTION
Bibliographic record
Abstract
had become an institution himself. With that loss the nature of the agency would begin to change, although no one could foresee the manner of change, so subtle were its beginnings. Allen Astin, leader of the Bureau for a decade and a half, was a scientist of the old school, not different in material ways from his four predecessors as Director: his most precious possessions were his scientific and personal integrity; his devotion to the institution was absolute; the efforts of his hours, days and years hewed to the goal of providing useful purpose for his staff and obtaining for them the best working environ-ment he could provide. In the exercise of his duties Astin had asked no quarter from his superiors. And in truth, he had received but little. A more desired commodity, however, he had been granted in abundance by all who crossed his path—respect for his ability and for his unflinching honesty. Our story begins with Astin's last year as Director. Most of his work is chronicled in the volume that serves as companion to this one. ' As we assess the institution that
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.123 | 0.039 |
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".