“Just letting you know … ” Underestimating others’ desire for constructive feedback.
Bibliographic record
Abstract
People sometimes avoid giving feedback to others even when it would help fix others' problems. For example, only 2.6% of individuals in a pilot field study provided feedback to a survey administrator who had food or lipstick on their face. Five experiments (N = 1,984) identify a possible reason for the lack of feedback: People underestimate how much others want to receive constructive feedback. Initial experiments demonstrated this underestimation of others' desire for feedback in hypothetical scenarios (Experiment 1), recalled feedback experiences (Experiment 2), and real-time feedback among friends (Experiment 3). We further examine how people ascertain others' desire for feedback, testing how much they consider the potential consequences of feedback for themselves (e.g., discomfort giving feedback or harm to their relationship with the receiver) or the receiver (e.g., discomfort receiving feedback or value from feedback). While we found evidence that people consider both types of consequences, people particularly underestimated how much receivers value their feedback, a mechanism not extensively tested in prior research. Specifically, in Experiment 4, two interventions-making feedback-givers consider receivers' perspectives (enhancing consideration of receivers' consequences) or imagine someone else providing feedback (reducing consideration of givers' consequences)-both improved givers' recognition of others' desire for feedback compared to no intervention, but the perspective-taking intervention was most effective. Finally, Experiment 5 demonstrates the underestimation during a financially incentivized public-speaking contest and shows that giving less constructive feedback resulted in less improvement in feedback-receivers' performances. Overall, people consistently underestimate others' desire for feedback, with potentially negative consequences for feedback-receivers' outcomes. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".