The Impact of COVID-19 on Transportation of Adults With Visual Impairments
Bibliographic record
Abstract
Introduction: Access to efficient and affordable transportation options has long been a challenge for many individuals with vision loss. In spring 2020, the COVID-19 pandemic caused a quick shift in the availability and safety of transportation. Methods: Using the constant comparison method, open-ended responses from 1,162 participants in the Flatten Inaccessibility study were coded. Responses were from participants who had concerns about transportation. Results: Ten themes and corresponding subthemes emerged from the data. Themes were interdependent in that the extent of concerns differed based on respondents’ support networks, transportation availability, and financial circumstances. Discussion: The COVID-19 pandemic brought to the forefront both systemic and COVID-19 transportation challenges about which those with visual impairments experienced or had concerns or both. Implications for Practitioners: It is imperative that professionals support those with visual impairments to develop alternative plans for when their typical transportation options are disrupted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".