Bibliographic record
Abstract
Abstract This article studies the Hope–Princeton Highway, a regional route in the province of British Columbia (BC), Canada, through the lens of uneven mobilities. Bringing together insights from infrastructure studies, mobility studies, and settler colonial studies, uneven mobilities is a concept that historicizes mobility research in terms of colonial and carceral logics. Using this concept, the article provides insight into political actors, namely incarcerated forced laborers of Japanese descent, whose unjust confinement and forced labor on this infrastructural route remained unacknowledged until recently. The article relies on a range of archival sources that engage the visual culture of the highway and the subtle linkages between an imagined scenic landscape and an imagined multicultural Canada. The article also narrates this highway route by constructing pictorial and landscape relationships of colonialism and carcerality, linking it to uneven mobilities and economic development through the ubiquitous highway road sign—a contemporary initiative to mark and interpret sites of historical and cultural importance along this and other BC routes. The article then explores the infrastructural politics of this route at the scale of the body to highlight modes of resistance. This article advances a tentative theory of uneven mobilities by centering so-called road disturbances through acts of resistance such as rest, play, and work stoppages to reveal how uneven mobilities are entwined with the production of embodied subjectivities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".