Bibliographic record
Abstract
American Association For Public Opinion Research Annual Membership Meeting The AAPOR annual membership meeting took place on May 20, 2006, at the Hilton Bonaventure Hotel, Montreal, Quebec, Canada. President Cliff Zukin called the meeting to order at 4:20 p.m. There were approximately 90 attendees. President Cliff Zukin welcomed the attendees and introduced the Executive Council members for 2005–2006: Nancy Belden—Past President Rob Daves—Vice President/President Elect Jennifer Rothgeb—Secretary-Treasurer Paul Beatty—Associate Secretary-Treasurer David W. Moore—Conference Chair Patricia Moy—Associate Conference Chair Nancy Mathiowetz—Standards Chair Thomas Guterbock—Associate Standards Chair Brad Edwards—Membership and Chapter Relations Chair Kat Draughon—Associate Membership and Chapter Relations Chair Shapard Wolf—Publications and Information Chair Steve Everett—Associate Publications and Information Chair Susan Pinkus—Senior Councilor-at-Large Robert Shapiro—Junior Councilor-at-Large Cliff Zukin praised the members of the council for their hard work and professionalism, and he particularly thanked those who were concluding their terms on council. Zukin reported on the activities of the...
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.321 | 0.239 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".