Bibliographic record
Abstract
<JATS1:p>We all wait – in traffic jams, passport offices, school meal queues, for better weather, an end to fighting, peace. Time spent waiting produces hope, boredom, anxiety, doubt, or uncertainty.</JATS1:p> <JATS1:p>Ethnographies of Waiting explores the social phenomenon of waiting and its centrality in human society. Using waiting as a central analytical category, the book investigates how waiting is negotiated in myriad ways. Examining the politics and poetics of waiting, Ethnographies of Waiting offers fresh perspectives on waiting as the uncertain interplay between doubting and hoping, and asks "When is time worth the wait?" Waiting thus conceived is intrinsic to the ethnographic method at the heart of the anthropological enterprise.</JATS1:p> <JATS1:p>Featuring detailed ethnographies from Japan, Georgia, England, Ghana, Norway, Russia and the United States, a Foreword by Craig Jeffrey and an Afterword by Ghassan Hage, this is a vital contribution to the field of anthropology of time and essential reading for students and scholars in anthropology, sociology and philosophy.</JATS1:p>
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.015 | 0.017 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".