The Power of Pictograms: a study and guide on how to create inclusive navigational signage using pictograms to address low situational literacy
Bibliographic record
Abstract
The transmission of navigational language is increasingly communicated by icons and visual indices. The research in this paper will examine the question of how to design inclusive navigational signage using pictograms to address the differing literacy levels in the local language and script for urban public transportation. Through theory of semiotic analysis and examining international and historical case studies, principles of inclusive design will inform a signage system, which will be used to create a new proposed guideline. This guideline will inform digitally-implemented navigation communication in urban settings, such as Toronto’s Transit Commission (TTC) subway system and underground walkway, the PATH. Findings are used as case studies to illustrate the application of the system. The physical environment in which the pictogram systems are created for must be specific to that environment only and cannot be interchangeable, which may include cultural implications. Recognizing that this nuance exists, inclusive navigational signage will need to include supplemental modes of communication, such as QR codes, to address those knowledge gaps for individuals with low situational literacy who may not know the local language or culture.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".