Business improvement areas and the socio-cultural power of lobbying: Imposing market interests to affordable housing development
Bibliographic record
Abstract
While studies have shown that Business Improvement Areas (BIAs) manage and control their physical urban spaces to generate local economic growth, little work has examined how these organizations lobby for their market interests during key decision-making processes. Drawing from the pragmatic sociology of critique, this paper develops a theoretical framework to explain how political-economic power is socio-culturally encoded during local government decision-making processes. Socio-cultural power is defined through two interrelated processes: (1) interactional settings where social actors practice their critical capacity by drawing upon socio-historically created moral orders and (2) the extent to which institutional experts limit laypersons' critical capacity and successfully construct local realities to advance their agendas. This framework is applied to London, Ontario's Old East Village to show how the local BIA influenced two separate affordable housing development plans. Based on interviews, participant observation, and document analysis, the findings show that the Old East Village BIA strategically framed and co-opted community critiques of these developments in a way that justified their own market interests (more feet on the street) over the community's civic interests (the provision of affordable housing). This paper extends the BIA literature by demonstrating BIA influence over affordable housing development, local matters that are outside the purview of their commercial jurisdiction.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.049 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.006 |
| 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".