Bus drivers’ attitudes toward people with intellectual disabilities
Bibliographic record
Abstract
Objectives Very few studies have documented the attitudes of bus drivers who play an important role in encouraging people with intellectual disabilities (ID) to use public transport. The objectives of this study were to measure bus drivers’ attitudes toward people with ID, to document the related variables and to compare the attitudes of the drivers to the general publics.Methods Two questionnaires (ATTID and Q-Bus Drivers) were administered to 269 bus drivers to document their attitudes.Results The results of the ATTID show that the most positive attitudes were identified on the Discomfort factor while the least positive were found on the Sensitivity/Tenderness factor. These attitudes differed from those of the general public. The quality of relationships was the variable most strongly associated with attitudes. The ATTID’s results were corroborated by the Q-Bus Drivers questionnaire, which also revealed the presence of paternalistic and infantilizing attitudes.Conclusions Training and awareness-raising activities involving both bus drivers and people with ID could improve the former’s attitudes. Other studies are needed to document bus drivers’ attitudes and evaluate the impact of interventions targeting their attitudes. Such interventions may ultimately foster the use of public transport by people with ID and their social inclusion.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".