Bibliographic record
Abstract
<JATS1:p>Human species supremacy is one of the most persistent fictions at work in the field of modern British imperial history today.This open access collection challenges that assumption, and investigates what histories of empire look like if reimagined as the effect of biocultural, chemical and cultural processes, rather than the result of effectsbyhumans that have been visiteduponcultural landscapes, fauna and biomes.</JATS1:p> <JATS1:p>In understanding the boundaries between human and nonhuman worlds as porous and open to mutual transformation, and foregrounding interspecies interactions,Biocultural Empireseeks to understand the conditions of imperial power, experience and knowledge as a remix of ‘nature’ and ‘culture’. Bringing empire’s ‘biocultural histories’ to the fore, it asks imperial historians to reckon with an interpretative framework which refuses the sovereignty and boundedness of the imperial subject by seeing it as inseparable from its social and ecological formations. Through this biocultural framework this collection highlights how relentlessly the human species bias of western liberal thought persists at the heart of imperial projects and their histories, and offers a new anti-colonial method that represents a significant intervention in the field of British imperial history.</JATS1:p> <JATS1:p>The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com. Open access was funded by University of Illinois, USA and University of British Columbia, Canada.</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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".