Bibliographic record
Abstract
The Towers in the World, the World in the Towers t h i s b o o k e m e r g e d out of a unique creative documentary project called High rise, at the National Film Board of Canada (NFB).Highrise was a sevenyear experiment in documentary, communityengaged research and co creation in nonfiction storytelling using emergent technologies.The documentary makers who were part of the project were interested in the actual people who make up the growing density of the global suburbs (inspired originally by our own city of Toronto, Canada).We also wanted to learn how vertical lives -literally, residents of these suburbs living in highrise buildings -are entangled with digital infrastructures and systems.For Highrise, we did not follow the conventional documentary pro cess of first finding subjects and experts to interview for a film, then interviewing them based on our questions, and then disappearing into an edit suite to shape an argument.We were mandated instead by the NFB to experiment in both form and content.Inspired by the NFB's legendary Challenge for Change project in the 1960s and 1970s, we were challenged to build the project out of a process rather than defining the process by the end goal.Our process was informed by community based and crossdisciplinary methods of cocreation.The project grew out of relationships and community engagements rather than arriving with preset agendas.For seven years, our team of documentarians worked alongside archi tects, urban planners, housing activists, technologists, scholars, and, most importantly, highrise residents themselves.Together, we built relation ships over time, and in so doing, we also jointly built the framing, the questions, and the goals of each of the many projects that spilled out from
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.624 | 0.577 |
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".