Gatekeeping fare collection in late industrial urbanity: Infrastructural labour in the gate milieu of the Stockholm metro
Bibliographic record
Abstract
Metro stations around the world are equipped with gate infrastructure to collect fares from passengers. At the Stockholm metro, the regional authority replaced tripod turnstiles with electronic gates aiming to better prevent fare evasion and increase revenue following reduced public transport subsidies. In this article, I engage with the politics of fare collection by attending to the gate environment in metro stations as constituting a milieu designed to regulate circulation. Rather than examining the gate milieu through its upfront purpose of fare collection, I critically examine the urban political relations generated and foreclosed in encounters with the material and semiotic properties of the gates. The margin of indeterminacy presented as the gates’ doors slide open upon a ticket validation, invites passengers to assist the gates, in either blocking or letting pass the following passenger to get through. Together with the regional authority’s framing of fare evasion as a cause for a degrading public transport infrastructure, the gate milieu pulls passengers into performing the work of fare collection. As such, the gate arrangement individualises responsibility among passengers for the maintenance of the metro as a collective good. Ultimately, the gate arrangements and the moralized repertoire in which they are inscribed, reveal how fare collection infrastructure risks contributing to escalating urban injustices in times of late industrial urbanity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.023 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".