Bibliographic record
Abstract
While one should not necessarily judge this multipronged exploration and defense of public space by its cover, the featured photograph of artist Lisa Klapstock in a protective suit and rubber boots sitting on a discarded armchair on the garbage-strewn edge of a parking lot does much to set the stage for the contents within. The image raises questions about how human figures relate to marginal, often semi-abandoned spaces, whose ownership, to say nothing of use, is at best ambiguous. While Klapstock's work is based on Toronto, and the essays that follow likewise focus on Canadian landscapes, there is much crossover with the United States, where welcoming, generative public space is similarly often either deficient or beleaguered. Mark Kingwell's lead essay begins by claiming that public space is variously “the age's master signifier,” a “site of suspicion, stimulation, and transaction,” and “the basis of public discourse itself,” and yet also points out the seeming oddity that most of us are reluctant to admit that we don't really know what public space is (3). He goes on to question whether public space is a form of public good, how public are certain so-called public spaces, how porous or controlled are the transitions between public and private spaces, and, ultimately, how our identities as individuals and as societies are related to and change upon contact with public space. These are fundamental, provocative concerns, in many respects addressed by the essays that follow.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.109 |
| Scholarly communication | 0.021 | 0.017 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".