Bibliographic record
Abstract
This book speaks to political issues that lie at the intersection of indigenous studies, science studies, and legal studies, focusing in particular on the role of power in shaping the interaction of indigenous and western knowledge systems. Pursuit of knowledge of the natural world has long been politicized. In some cases this has been subdued, a matter of inflection; in others it has been more pronounced, a dominant and dominating agenda for research. The vital role of science as a part of statecraft has been underscored by numerous historians of science, who, in the latter part of the twentieth century, began to document the “issues of cultural and economic domination involved in the pursuit of natural knowledge.” The rule of law, they argue, was identified with the scientific method and became, for the West, a vital means of extending empire. The conduct of imperial science by nation-states during the late eighteenth and nineteenth centuries, and its effect upon other nation-states, has led historians of science to conclude that the issue is no longer science in imperial history but science as imperial history. My concern here is with the continuation of one strand of that history into the present, with how a new imperial science impacts, and is impacted by, indigenous peoples rather than nation-states. Certain areas of contemporary bioscience, currently in the service of western pharmaceutical and agricultural industries, are enabling the appropriation of indigenous knowledge and genetic resources at a prodigious and escalating rate. Opposition to such biocolonialism has not only been vigorous, but international in scope.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.608 | 0.514 |
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".