The Marginal Public: Marginality, Publicness, and Heterotopia in the Space of the City
Bibliographic record
Abstract
This thesis explores the experiences of an urban population who are considered to exist at the social margins of society, but who paradoxically spend much of their time in urban public space. Often referred to as ‘street people,’ the issues they face, such as homelessness and drug addiction, become public issues. In this thesis, I introduce and develop the concept of the marginal public to refer to this population, exploring their experience of the city not through the lens of their marginalization but through their relationship to the spatial and social realms of urban life. I explore the ways in which the marginal public, through their visibility and presence in the city, are not marginal to urban life but deeply embedded in it. Their marginality is lived simultaneously yet in contestation with dominant ways of being. This manifests in the marginal public’s relationship to others in the city, as well as through debates about the placing of facilities that serve them which I explore through the unsanctioned supervised consumption site of Overdose Prevention Ottawa (OPO). Finally, through the concept of heterotopia, I explore the margins as places of otherness as well as possibility.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.049 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".