“I am the first of my kind to see it”: Observation and Authorship in Mina Hubbard’s Performance as Labrador Explorer, 1905–1908
Bibliographic record
Abstract
Abstract: Cet article porte sur l’expédition réalisée en 1905 par la Canadienne Mina Hubbard à travers le Labrador et la péninsule d’Ungava. Ce faisant, il examine la notion d’explorateur/voyageur nordique non autochtone en tant que témoin. Il considère deux pratiques qui furent essentielles à Hubbard dans la construction et la mise en scène de son identité en tant qu’exploratrice : l’observation empirique et la publication de ses travaux. Les efforts de Hubbard pour se présenter comme une personne digne de témoigner des régions nordiques, en compétition avec ses guides des régions sauvages, mettent aussi en relief les types d’identités de race, de classes sociales et de genre qui étaient exclus de l’entreprise d’exploration des régions nordiques au tournant du siècle. Abstract: This article focuses on Canadian Mina Hubbard’s expedition through the Labrador-Ungava Peninsula in 1905. In so doing, it examines the notion of the northern non-Indigenous explorer/traveller as witness. It considers two practices that were essential to Hubbard in the construction and performance of her identity as an explorer: empirical observation and authorship. Hubbard’s efforts to present herself as a reliable northern witness, in contest with her wilderness guides, also highlight the kinds of racialized, classed, and gendered identities that were excluded from the work of northern exploration around the turn of the century.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.017 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".