Bibliographic record
Abstract
In the last decade the planning literature has reflected growing interest in the topic of gated communities. To date, this relatively new field of research has generated limited theoretical development. Although recent literature has begun to elucidate the social and economic contexts that make gated enclaves a global phenomenon, few works offer an overview of the physical features of gated communities. The key source articulating a framework for understanding gated communities is Blakely and Snyder's, Fortress America. Although Blakely and Snyder provide detailed findings on the form of gated projects in the US context, they say little about gating elsewhere. This paper draws on a range of literature on gated enclaves to examine and augment the typology created by Blakely and Snyder. Building theory to explain the form and character of gated communities requires the consideration of a range of historical experiences and international differences in practice. Although classification alone does not constitute theory, it provides an important foundation for those seeking to generate premises and principles for further theoretical development. It also offers useful tools for case studies of practice.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".