Bibliographic record
Abstract
There is a risk that modern practices of information communication and visualization in human-computer interaction can sideline communities due to their prioritization of scientific rationality. Such ideological hegemony can complicate interactions with data and computers, especially for low-literate communities in the global south. Through a six-month long ethnographic study with Nakshi-Katha makers, Hindu Idol makers, and witchcraft practitioners, we investigated how rural practitioners use their own forms of representation and narrative in record keeping, social and religious storytelling, and information mediated decision making. We find that traditionally developed approaches towards presenting and communicating information often make use of concrete units to represent entities and connect to designers' cultural practices and the physical location. Further, we identify how medium has significant influence in meaning-making. Often these strategies and conventions are passed down through generations within the community. In this paper, we discuss how this rural tradition differs from the modern information communication practices, discussing how an understanding of traditional practices for representing information can be useful in developing more accessible, and culturally appropriate modern tools and technologies for the people of rural Bangladesh and similar communities.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.018 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.064 | 0.010 |
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".