The intelligence of place : topographies and poetics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Notes on Contributors Introduction 1. Place and Edge, Edward Casey (Distinguished Professor of Philosophy at Stony Brook University, USA) 2. Place and Limit, Massimo Cacciari (Italian Institute for Philosophical Studies, Naples, Italy and the College de Philosophie, Paris, France) 3. Place and Histories - Writing Other People's Memories, Lucy R. Lippard (Free lance Writer) 4. Place and Time, Jeff Malpas (Distinguished Professor, University of Tasmania and Visiting Distinguished Professor, Latrobe University, Australia) 5. Place and Media, Joshua Meyrowitz (Professor of Communications, University of New Hampshire, USA) 6. Place and Atmosphere, Juhani Pallasmaa (Professor Emeritus, Juhani Pallasmaa Architects) 7. Place and Architectural Space, Alberto Perez-Gomez (Saidye Rosner Bronfman Professor in History and Theory of Architecture, McGill University School of Architecture, Canada) 8. Place and Connection, Edward Relph (Professor of Geography, University of Toronto, Canada) 9. Place and Sensory Composition, Kathleen Stewart (Professor of Anthropology, University of Texas at Austin, USA) 10. Place and Formulation, Kenneth White (Royal Scottish Academy, Professor of Twentieth-Century Poetics, Sorbonne, Paris) Index
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it