How Virtual Work Environments Convey Perceptual Cues to Foster Shared Intentionality During Covid-19 for Blind and Partially Sighted Employees
Bibliographic record
Abstract
The Covid-19 pandemic altered workplaces. For those with ‘office jobs,’ this meant working ‘virtually,’ or remotely, from home. This transition forced organizations and workplaces to exercise flexibility, adapt workflows and rely on Information and Communication Technologies (ICTs) to work remotely. However, Blind and Partially Sighted Individuals (BPSI) face challenges accessing work digitally and remote communications through ICTs. In response, we report on the results of our longitudinal participatory design study investigating the impact of working and training over a distance for BPSI. What emerged is a conceptual model to assist in understanding how ICT interfaces convey spatial-topological cues for the construction of shared intentionality in virtual work environments. The implications of our model could be significant, as it aids understanding of what is lost and gained when transitioning to virtual work environments. This could inform the development of ICTs with cross-sensory interaction and national accessibility policies for the workplace.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".