Parareligious-HCI: Designing for 'Alternative' Rationality in Rural Wellbeing in Bangladesh
Bibliographic record
Abstract
A body of Human-Computer Interaction (HCI) research addresses a wide range of wellbeing issues including digital and online health-care, formal and informal healthcare and wellbeing infrastructure, and health informatics. We focus on the wellbeing practices among the underrepresented marginalized communities in rural Bangladesh. The goal of this work is to understand their wellbeing challenges and how those are connected to their religious beliefs and adaptations - that we define as 'Parareligion'. This paper presents our findings from a 3-year long ethnographic study with 150 participants in 15 villages. We extend this discussion by arguing for better inclusion of para-religious practices in Wellbeing-HCI discourse to design more culturally appropriate and sustainable technologies for such target 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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".