Forgiven But Not Forgotten: Covert Uncertainty in Overt Responses and the Paradox of Defection‐Despite‐Trust
Bibliographic record
Abstract
Despite the widespread belief that trust is a critical determinant of loyalty, empirical and anecdotal evidence calls into question the real‐world robustness of the trust–loyalty link. An important reason for the fuzzy nature of the trust–loyalty link may be the fuzzy nature of trust itself. That is, stated trust judgments embody both a magnitude dimension (i.e., the position along a favorable‐unfavorable continuum) and an uncertainty dimension (i.e., the lack of conviction with which the judgment is held). We investigated this possibility using data pertaining to consumers’ reactions to a service failure and the provider's success in responding to their complaints. We found that the interplay between dissatisfaction with the complaint handling and past experience simultaneously influences trust magnitude and trust uncertainty. However, these two dimensions of trust are shaped by different underlying processes. Finally, uncertainty dampens the impact of stated trust on loyalty.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".