Bibliographic record
Abstract
Half a century of explosive suburban expansion has fundamentally changed the \nmetropolitan dynamic in North American city-regions. In many cities the imagined \nsuburban “bourgeois utopias” that evolved during the 19th Century, in material and \ndiscursive opposition to the maladies of the city, have given way to diverse forms of \nsuburban and exurban development. New, complex and contradictory landscapes with \ndiverse social, infrastructural and political-economic characteristics have appeared \nwithin pre-existing urbanisms and urban forms. This maelstrom of growth, with its \nassociated fluid geographical restructuring, is being reflected in qualitatively different \nrhythms of everyday suburban life and has engendered stresses in the institutional and \ninfrastructural cohesion of the metropolis – problematizing scalar governmental \nrelations between city and suburbs, the theoretical and applied use of “urban” solutions \nto address “suburban” problems, and what constitutes “urbanity” itself. \nFocusing on the Canadian context from a broad (yet by no means exclusive range of \nmethodological and theoretical perspectives, it can be argued that, despite their \nubiquitous presence, suburban society, space and politics have been unduly sidelined in \nvarious bodies of geographic literature. In response to this deficit, we think it is time to \ndevelop a research agenda for critically unpacking the complex social, institutional and \ninfrastructural realities of contemporary suburban landscapes. In particular, we suggest \nfuture studies of “the suburbs” may benefit by engaging with the following: (1) the \ncontinuing predominance of an uncritical city-suburb dichotomy; (2) the presence of “inbetween landscapes”, poorly acknowledged in both urban and suburban imaginaries; (3) \nthe theoretical de-valorization of “forgotten” suburban spaces and lives within the \ncontemporary metropolis; and (4) the dialectical interplay between (sub)urban society, \nspace and politics. A re-conceptualisation of “the suburbs” requires a holistic \nunderstanding of the city’s varied landscapes, everyday realities, and contemporary \npolitical infrastructures, allowing us to grasp the fluidity and dynamism (and emerging \ncontradictions) shaping present-day urban experiences in Canadian city-regions.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.046 | 0.014 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".