“We embrace winter here”: Celebrating place in winter cities
Bibliographic record
Abstract
Weather is an elementary and fundamental characteristic of place. In any given place we encounter the materiality of weather, local meanings attached to weather, and practices adopted in response to living with weather. Winter cities are places defined by their weather—long, cold winters that can pose challenges to urban life. Efforts to address these challenges centre on place‐making activities, such as seasonal festivals, which seek to enrich public spaces. In this paper, we examine the relationship between winter, place, and placemaking in three Canadian prairie cities. Participants sought to promote a celebratory relationship with winter by changing public attitudes, fostering unique winter experiences, and incorporating winter into their cities’ identities. This shift was encouraged by strategies and events that were “authentic” to local context and community. They did not simply reframe winter weather as positive, but recognized the season as presenting both challenges and opportunities. Enabling residents to realize opportunities is critical to being a successful winter city, and requires negotiating a set of dyads: warm/cold, indoor/outdoor, and light/dark. This paper highlights the constitutive role of weather in shaping place, while revealing the agentic ways in which communities act towards and with weather.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.015 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".