Bibliographic record
Abstract
Recent debates about the health of First Nations peoples have drawn a flurry of public attention and controversy, and have placed the relationship between Aboriginal well-being and reserve locations and allotments in the spotlight. Aboriginal access to medical care and the transfer of funds and responsibility for health from the federal government to individual bands and tribal councils are also bones of contention. Comprehensive discussion of such issues, however, has often been hampered by a lack of historical analysis. Promising to remedy this is Mary-Ellen Kelm’s Colonizing Bodies, which examines the impact of colonization on Aboriginal health in British Columbia during the first half of the twentieth century. Using postmodern and postcolonial conceptions of the body and the power relations of colonization, Kelm shows how a pluralistic medical system evolved. She begins by exploring the ways in which Aboriginal bodies were materially affected by Canadian Indian policy, which placed restrictions on fishing and hunting, allocated inadequate reserves, forced children into unhealthy residential schools, and criminalized Indigenous healing. She goes on to consider how humanitarianism and colonial medicine were used to pathologize Aboriginal bodies and institute a regime of doctors, hospitals, and field matrons, all working to encourage assimilation. Finally, Kelm reveals how Aboriginal people were able to resist and alter these forces in order to preserve their own cultural understanding of their bodies, disease, and medicine. This detailed but highly readable ethnohistory draws on archival sources, archeological findings, fieldwork, and oral history interviews with First Nations elders from across British Columbia. Kelm’s cross-disciplinary approach results in an important and accessible book that will be of interest not only to academic historians and medical anthropologists but also to those concerned with Aboriginal health and healing today.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.045 | 0.006 |
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".