People Transitioning Across Places
Bibliographic record
Abstract
Stokols and Shumaker suggested that places can be characterized in terms of whether they are occupied primarily by individuals, aggregates, or groups. The authors propose a fourth type of place, one occupied primarily by groups within an aggregate. This research used a multimethod approach to examine whether people go to football games alone or with others and, if with others, how many others. Observations of cars entering parking lots or parking decks indicated that on average each vehicle contained about 2.5 individuals. Surveys of individuals about to enter the stadium also indicated that on average people were in groups of about four. Computer vision tracking of pedestrians next to the stadium about 2 hr before the game indicated that, although about one quarter of the pedestrians were alone, groups averaged about four. Thus, the results suggested that informal groups became larger as a function of proximity to the stadium. Analyses of the space occupied by groups of different sizes indicated that as groups got larger, the amount of space per person got smaller. These results, which indicate that people go to football games in small groups, have implications for the built environment and security.
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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 | 0.000 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".