"Swee-ee-et Cán-a-da, Cán-a-da, Cán-a-da": Sensuous Landscapes of Birdwatching in the Eastern Provinces, 1900–1939
Bibliographic record
Abstract
Birdwatching emerged as a popular Canadian pastime as rapid industrialization and urbanization encroached on rural and wilderness landscapes at the end of the nineteenth century. This paper analyses birdwatching as a bodily engagement with place and a sensuous transformation of material setting into landscapes of personal and collective identity. Focusing on the development of activities such as Nature Study and camera hunting, we argue that birds linked people to specific places and that these relationships helped (re)define national identities and landscapes in eastern Canada. In attending to ways in which sensuous experience of birds has been informed by normative and nationalistic discourse, we also begin to trace the imaginative and moral geographies that have placed birds in idealized landscapes, protected zones and categories such as native and foreigner. Resume L'observation des oiseaux est devenue un loisir populaire au Canada lorsque l'industrialisation et l'urbanisation ont empiete sur les campagnes et les paysages inexplores a la fin du XIXe siecle. Cet article examine ce passe-temps sous l'angle du rapport physique avec un lieu et de la transformation par les sens de cadres materiels en paysages d'identite individuelle et collective. En se concentrant sur l'emer gence d'activites telles que « l'observation de la nature » et « la chasse aux images », les auteures soutiennent que les oiseaux ont relie les gens a des endroits determines et que ces liens ont contri bue a (re)definir identites nationales et paysages dans l'Est du Canada. En considerant les facons dont l'experience sensorielle vecue avec les oiseaux a influence les discours normatifs et nationalistes, elles relevent les geographies morales et imaginatives qui ont « place » les oiseaux dans des paysages idealises, des zones protegees et des classifications en oiseaux « indigenes » et « etrangers ».
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".