“You’ll probably tell me that your grandmother was an Indian princess”: Identity, Community, and Politics in the Oral History of the Union of British Columbia Indian Chiefs, 1969-1980
Bibliographic record
Abstract
Oral history interviews with current and former members of the pan-tribal political organization the Union of British Columbia Indian Chiefs (the Union) provide important insight into both the history of the modern BC Indian movement, as well as the nature of oral interviews themselves. This article examines how narrators of Union history discuss contentious twentieth century political concerns, keeping in mind the continued currency of these issues. This study argues that oral history interviews are negotiated political spaces wherein historiographical and political interpretations are debated between interlocutors and involved listeners. As such, oral interviews of Union members are political on a personal level, whereby narrators engage with the listener to navigate multiple and shifting positions, the relationship between academy and community, and shared knowledge in order to create an acceptable interview space. They are also political in a historiographical sense, in that narrators use the interview to negotiate with their own memories as well as with other activists to produce, debate, and shape the narrative of the Union. This article challenges the prevailing tendency of oral historians to emphasize concepts of collaboration and stable identities in oral history research, and reveals how oral histories of Indigenous protest movements complicate these relationships and the resulting historical narrative.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.016 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".