Visualizing the Canadian Prairies: Photographic Representations of Rurality
Bibliographic record
Abstract
Who is the rural prairie dweller? What do their communities and landscapes look like and how are they changing? The rural is often placed in a position outside modernity, often thought of as backward, a fading condition, and written-off as a site of little interest. With the recent rise of conservative populism comes an imperative to produce accessible, searching, prying, and emotive scholarship for understanding the rural condition. Visualizing the Canadian Prairies explores depictions of the rural condition by adopting an interdisciplinary and multi-modular approach, which utilizes elements of visual sociology and arts-based research as a way to explore and challenge presumptions of prairie space. \n \nThe project blends a production-orientated approach that is informed by a photography-centric history of Western Canada. Utilizing photographic and archival materials focused on rural spaces, the dissertation creates a visual and theoretical account of changes in rural representation of Alberta since 1980. Image and text based narrative sections of the dissertation are the result of numerous and extensive field research trips. In addition to personal observations and community photographs, the dissertation also draws upon Canadian image-makers, social theorists, and historians to provide additional context, beginning with the celebrated first photograph of the prairies in 1858, and a series of 20th and 21st Century photography projects. \n \nEach of the three body chapters are composed of three disparate but interconnected elements: analysis, visual narrative, and written narrative; distinctions that aim to blend textual and visual didactic and analytical forms with creative non-fiction. The chapter titled Digging In challenges a provincialist framework by exploring the 1980 documentary project Keepsake, and first introduces the concepts of rural banality and the rural as a significant site of regional heritage. Mapping Out adopts the framework of regionalism by focusing on the regions contemporary image-makers and their relation to space and landscape. While another chapter, titled Returning To, uses a framework of localism and ideas of post-photography to develop a case-study of a specific prairie town, as a way to deconstruct ideas of ruralism through an alternative history of Place.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".