Keynote: Eve Blau, Harvard University Graduate School of Design
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
Eve Blau is Adjunct Professor of the History and Theory of Urban Form at the Harvard University Graduate School of Design. Her research engages a range of issues in urban and architectural history and theory and the productive intersection of urbanism and media. She is Co-Principal Investigator of the Harvard Mellon Urban Initiative, an interdisciplinary cross-school initiative supported by funding from the Andrew W. Mellon Foundation. It brings together scholars and resources from across Harvard to foster interdisciplinary urban study through collaborative research and teaching, and by developing innovative cross-disciplinary methodologies that integrate digital technologies to bring together the perspectives of the design disciplines, the humanities, and the social sciences. In 2015 Blau received the Victor Adler-State Prize of the Republic of Austria in recognition of her innovative scholarship and contributions to the history of social movements. Before Harvard, Blau was Curator of Exhibitions and Publications at the Canadian Centre for Architecture in Montreal, and Editor of the Journal of the Society of Architectural Historians. She is President of the Board of Directors of the American Friends of the Canadian Centre for Architecture, Montreal and past Vice President of the International Scholarly Advisory Board of the IFK Internationales Forschungszentrum Kulturwissenschaften (International Research Center for Cultural Studies) Vienna, and Fellow of the Society of Architectural Historians.
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.843 | 0.995 |
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