Nothing from something from nothing: in response to ‘conspiracy thinking about the 15-minute city: something from nothing?’Rien à partir de quelque chose à partir de rien : une réponse à « Conspiracy thinking about the 15-minute city: Something from nothing? »
Bibliographic record
Abstract
In this response piece, I provide an assessment of a recent article focused on conspiracy theories and the 15 min city planning concept. While the original article focuses on addressing, deconstructing and debunking false narratives surrounding the 15-min city, I provide a critique of the tone, content and approach employed in doing so. My goal is not to discount or discard the valid points made in the original piece, but rather to emphasize how (in keeping with this special issue) some subtle changes would allow us to ‘bridge divides … generate solidarity … and work to (re)build social structures in ways that nurture’ through a more evenhanded approach. Although this response is focused on a single article, I see this piece as a critique of leisure studies more broadly and hope to raise some questions about the ‘responsibility of leisure scholars in an age of misinformation, alternative facts, and post truth’.
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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.026 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.009 | 0.018 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".