Ontological locationalities: Moving beyond North–South binary and interrogating what gets studied
Bibliographic record
Abstract
Recent calls in urban studies emphasize the need for inquiry to look beyond North Atlantic circuits of knowledge production, encouraging research to venture beyond the metropolis. These calls advocate engagement with empirical and theoretical insights from multiple elsewheres that have been conceptualized as peripheries. In this article, I contend that more studies from peripheries would not alter the North Atlantic knowledge hegemony, as the ontological locationality of these endeavours remain metropolitan. I argue that we first require distinctive formats, methods, and theories to discuss where our concerns arise from: it is crucial to recentre and re-contextualize uniquely positioned researchers within the particular circumstances of contemporary urbanization processes. Thereafter, I propose the possibilities for pluriversal urban theories and dialogues, to be able to at least start the process of dislocating the ontological hegemony of the metropolis, which embodies the power to decide what is there to be known from these peripheries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".