Trustworthy Virtual Advisors and Enjoyable Interactions: Designing for Expressiveness and Transparency
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
Online virtual advisors have enjoyed an increased research attention and widespread use in the last several years. In investigating the determinants of their adoption, the majority of extant research has focused on a set of utilitarian variables that address some outcomes from their use. In contrast, this study focuses on users’ perceptions of these virtual advisors as interaction partners, and on beliefs users form during these interactions. Specifically, we propose and test for the effects of perceived advisor expressiveness and transparency on perceptions of their trustworthiness and interaction enjoyment. The latter two constructs are further proposed to act as antecedents to users’ reuse intentions. The results of an experimental study lend support to the proposed model, and highlight the importance of designing social and trustworthy advisors and enjoyable interactions.
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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 | 0.002 | 0.001 |
| 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 | 0.001 | 0.002 |
| 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 it