Bibliographic record
Abstract
Fur: A Sensitive History is the first broad socio-cultural history of fur that encompasses not only fur’s fashionable history but also its economic, psychological, and artistic importance. Due to fur’s current controversial status, not only are there no authoritative and, most importantly, unbiased accounts of this historically important subject, but its rich and complex history is in danger of being forgotten amidst the increasingly polarized arguments of the pro and anti fur lobbies. Fur has built nations; inspired great works of art and literature, has led to the near destruction of certain species and has signalled status, glamour and power. This is the first book to try and understand this most supremely tactile, and sensitive of subjects, that has been a source of inspiration for Western fashion since the Middle Ages. In this book our attraction to, and indeed rejection of fur is understood by comparing animal and human hair. The history of the anti-fur movement is traced back to early human and animal rights organisations, a fascinating early history that has been overshadowed by the activities of more recent anti-fur protests. Fur’s centrality to the social and economic regulation of western society is discussed, as is the demand for fur, which has driven colonial exploration and exploitations in search of fur, especially through the North American and Canadian fur trades. Fur’s transformative properties are considered via its presence in myth, literature and film, whilst its tactile and visual stimuli are understood by considering fur’s erotic appeal. Combining high art and popular culture with a visual account consisting of many never before seen images the book reveals, without advocating its use, fur’s importance to global history and culture.
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 | 0.002 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".