Trust in interaction studies
Bibliographic record
Abstract
Trust is argued to be essential in fostering cooperative communication, whereas a lack of trust is seen as detrimental to these aims. Over the years, there has been a slow but steady stream of research that has aimed to shed light on how trust is accomplished or broken down through discursive-interactional practices. In this mini review, we examine existing studies that take trust as a topic of investigation using micro-analytic, interactional methods, in order to provide readers with an up-to-date overview on new developments in this important field of research. From this review, we conclude that there exist two different, yet complementary, views on trust: Trust as an interactional principle and trust as a discursively accomplished phenomenon. We not only summarize important discursive work that provides a unique lens on how trust may be established and maintained through verbal and non-verbal resources, but also suggest some of the challenges interactional trust research still faces and some important areas for further investigation in which trust is a major concern.
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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 | 0.030 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".