Maureen A. Flanagan. Constructing the Patriarchal City: Gender and the Built Environments of London, Dublin, Toronto, and Chicago, 1870s into the 1940s.
Bibliographic record
Abstract
Why do cities in the transatlantic Anglophone world share many distinctive characteristics? The answer, according to Maureen A. Flanagan, has everything to do with the protection and promotion of male privilege. In Constructing the Patriarchal City: Gender and the Built Environments of London, Dublin, Toronto, and Chicago, 1870s into the 1940s, Flanagan reveals how leading men in four cities—London, Dublin, Toronto, and Chicago—wielded their political and financial influence to establish a metropolitan landscape that upheld their own ideals of masculinity, femininity, and the separation of spheres. Their approach to urban development prioritized efficiency, order, and economic growth. Moreover, it typically diverged from the perspectives advanced by female reformers, who were inclined to emphasize health, safety, and social harmony. Focusing on the period between 1870 and 1940, Flanagan compares the urban solutions proposed by activist men and women to problems caused by industrial growth, from overcrowding and homelessness to traffic congestion and poor sanitation. At nearly every turn, Flanagan argues, men’s plans for urban improvement conflicted with—and, ultimately, prevailed over—those of women. The result in all four cities was a built environment that gave material form to patriarchy.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".