10.1177/0891241605279839JOURNAL OF CONTEMPORARY ETHNOGRAPHY / DECEMBER 2005Shaffir, Kleinknecht / DEATH AT THE POLLS DEATH AT THE POLLS Experiencing and Coping with Political Defeat
Bibliographic record
Abstract
of a number of scholarly books and articles in the areas of hassidic and haredi Jewry, occupational socialization, and field research methods. His Web site featuring a particular hassidic sect may be found at www.kiryastash.ca. His current projects include a study of diversity training and management in a Canadian metropolitan police force and a documen-tary on the Jewish community of Hamilton, Ontario, Canada. STEVEN KLEINKNECHT is a doctoral student in the Department of Sociology at McMaster University. His research interests lie in the study of qualitative methods, subcultures, deviant behavior, online inter-action, and social problems. His recent research pro-jects include ethnographic studies on the hacker sub-culture and social change within Old Order Menno-nite communities. He has also worked as a research analyst at the Department of Justice Canada where he has written on issues pertaining to restorative justice, juvenile justice, and cybercrime. “It’s a sudden stop. It’s just like somebody shut off the tap. It just ends. It’s over. It’s death.”
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.826 | 0.573 |
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".