Understanding Tabletop Games Accessibility: Exploring Board and Card Gaming Experiences of People who are Blind and Low Vision
Bibliographic record
Abstract
Gaming accessibility research for blind or low vision (BLV) communities largely focuses on digital games. There is a need for designers to understand BLV's experience with tabletop games that involve the player's physical interaction. In this study, we investigate BLV individuals’ experience with the accessibility of tabletop games. We conducted semi-structured interviews with 15 BLV participants and found four themes that uncovered participants’ tabletop gaming experiences: (1) properties of inaccessible games, (2) outcomes of inaccessible games, (3) properties of accessible games, and (4) outcomes of accessible games. Our findings demonstrate a richness and variety in BLV individuals’ tabletop gaming experiences. By providing discussions on the state of tabletop game interactivity and design recommendations, our work assists the creation of accessible tangible games that make use of digital information and physical forms by affording designers the opportunity to understand how inaccessible interactions in tabletop games affect BLV populations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".