Bibliographic record
Abstract
PURPOSE: Although stair use in workplaces can provide an accessible means of integrating physical activity into work routines, there is little information available on how building design influences stair use. DESIGN: This cross-sectional study assessed the relationship between stair use and the design and location of stairs. SETTING: Ten three- or four-story academic buildings on two university campuses. SAMPLE: The buildings contained a total of 38 stairs and 12 elevators. MEASURES: Stair use was measured using infrared monitors. Eighteen environmental variables that operationalized the appeal, convenience, comfort, legibility, and safety of stairs were measured. RESULTS: Regression analysis identified eight spatial variables associated with stair use: travel distances from stair to nearest entrance and the elevator, effective area or occupant load of each stair, accessibility of each stair, area of stair isovist (a graphic representation of the horizontal extent of a person's visual field from a specific point of reference within a building floor plan), number of turns required for travel from the stair to closest entrance, and the most integrated path (MIP). Three variables (effective area, area of stair isovist, and number of turns for travel from the MIP), explained 53 % of stair use in the 10 buildings. Most variables operationalizing the appeal, comfort, and safety of stairs were not statistically influential. CONCLUSIONS: This study suggests that the spatial qualities that optimize the convenience and legibility of stairs may have the most influence on stair use in buildings.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".