A Spindle, an Awl, and the Construction Tools of Tla’amin Histories in the Twentieth Century
Bibliographic record
Abstract
Western historical and ethnographic scholarship has tended to overlook Indigenous people’s processes of making handmade items in favor of focusing on the finished objects. This neglect obscures the social, political, labor, and gender histories of the items. For members of the Tla’amin Nation in British Columbia, Canada, histories of tools show how processes of making objects have also been processes of making histories. Histories of making objects help to show how community members retained and actively defended their agency: tools enabled community members to make their presence visible in a larger colonial climate that sought to erase them. This article responds to calls from Indigenous scholars to analyze power and gender dynamics that are inherent within histories of objects themselves, as well as within community members’ own experiences. Oral histories and a traditional use study (TUS) conducted in Sliammon in the late 1990s historicize the significance of tools that contemporary community members have discussed. These phenomena of economic change, politics, and tradition have all been inherent themes in histories of making things in Sliammon. Such inherent themes become explicit with a focus on tools as construction tools of histories, and they show how tools have been central in Tla’amin responses to colonial incursions past and present.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.028 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".