Bibliographic record
Abstract
In what ways do paces of movement shape places, and how do different places shape their movements’ paces? The objective of this paper is to provide exploratory answers to these questions by focusing on the mobility constellations of ferry-dependent islands and coastal communities of Canada’s west coast. I focus on the slower temporalities and spatialities of mechanized technologies of mobility by drawing upon research conducted for a larger ethnographic project aimed at understanding the multiple roles played by ferry mobilities in the lives of British Columbia’s ferry-dependent islands and coastal residents. Boats’ rhythms, speed, and the duration of journeys occasion the conditions for the cultivation of an empirically unique region-specific sense of time. Within this ethnographic context ferry boats serve as technologies through which residents of island and coastal communities weave distinct place temporalities and mobility constellations. Islanders and coasters employ the affordances of ferries to break away from the place temporalities typical of the city. Such movement toward separation from the urban is what I refer to as moving ‘out of time’. Moving ‘out of time’ is done in order to tune into the alternative insular and coastal temporal regimes deemed more desirable by the locals. Such movement toward attunement is what I refer to as moving ‘in time’.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".