Creating Religious Spaces in Cape Town, Barcelona and Montreal: Perspectives from Cultural Theory on the Re-Figuration of Spaces and Cross-Cultural Comparison
Bibliographic record
Abstract
Engaging with recent social science debates on urbanism, space, and religion, in this article I explore how religious change and the re-figuration of spaces are mutually shaped in cities located on three different continents: Cape Town, Barcelona, and Montreal. I start from the premise that social actors' spatial strategies and existing spatial regimes with regard to urban religion are mediated by the ways in which state and non-state actors draw on and mobilize publicly circulating notions of religious diversity and secularity. My argument is that there are, at the current conjuncture of global religious change, three main processes affecting the re-figuration of spaces: 1. the eventization, 2. the infrastructuration, and 3. the heritagization of religion. While they carry global significance, these processes play out differently in the three cities I analyzed. By identifying these shared developments, I challenge the notion that links between urbanism and religion in the Global South and the Global North are different beyond comparison. Instead, I argue that comparative methodologies in studies on urban religion are indispensable in order to reveal both global structural forces and cultural differences. The article is based on my ethnographic fieldwork carried out in each of the three cities.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.027 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".