Persuasive interaction for collectivist cultures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Persuasive technology is defined as any interactive product designed to change attitudes or behaviours by making desired outcomes easier to achieve. It can take the form of interactive web applications, hand held devices, and games. To date there has been limited research into persuasive technology outside of America. Cross-cultural research shows that in order for persuasion to be most effective, it is often necessary to draw upon important cultural themes of the target audience. Applying this insight to persuasive technology, we claim that the set of persuasive technology strategies as described by B J Fogg caters to a largely individualist audience. Drawing upon cross-cultural psychology and sociology findings about patterns of behaviour commonly seen in collectivists, we present a principled set of collectivism-focused persuasive technology strategies. These strategies are: group opinion, group surveillance, deviation monitoring,disapproval conditioning, and group customisation. We also demonstrate how application of the strategies can support the design of a collectivist, persuasive game.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it