A Critical Perspective on the Current State of Collective Housing. A Conversation with Carmen Espegel
Bibliographic record
Abstract
Carmen Espegel is Professor of Architectural Projects at the Higher Technical School of Architecture of the Polytechnic University of Madrid (ETSAM). Her career has encompassed three closely interrelated fields of activity: teaching, research and the profession of an architect. With her published works and her design projects she has bridged the gap between critique and practice of architecture, specifically, contemporary collective housing. Her profound knowledge drives apart from the purely theoretical and offers the viewpoint of a seasoned architect. She leads the Master of Advanced Architecture in Madrid and the Master in Collective Housing, which is jointly run by the Polytechnic University of Madrid and the Swiss Federal Institute of Technology in Zurich. She has collaborated with numerous universities in Europe, South America, the United States and Canada—this interview took place in Quebec, where Carmen is Visiting Professor at the city’s Laval University. Her research activity, focused on three fundamental branches—collective housing, critical theory and women and architecture—has driven her to lead the Collective Housing Research Group (GIVCO) and capture her critical thinking, with an important contribution in the area of residential design. In her role as a professional architect, her extensive and wide-ranging activity in tenders and works, which have received international recognition and awards, complements her incursions on the present-day manifestations of habitat, contributing to its development. Our conversation is organised in several themes that serve to connect personal reflections and aspects on the contemporary alternatives inherent in collective housing.
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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 | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.036 | 0.056 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 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".