Pitch as a Recipient, Channel, and Context Factor Affecting Thought Reliance and Persuasion
Bibliographic record
Abstract
Three experiments tested how low versus high pitch generated from sources beyond a message communicator can affect reliance on thoughts and influence recipients' attitudes. First, participants wrote positive or negative thoughts about an exam proposal (Experiments 1, 2) or their academic abilities (Experiment 3). Then, pitch from the message recipient (Experiment 1), channel (Experiment 2), or context (Experiment 3) was manipulated to be high or low. Experiment 1 showed that when participants vocally expressed their thoughts using low (vs. high) pitch, thoughts had a greater effect on attitudes toward exams. Experiment 2 revealed low (vs. high) pitch sounds from the keyboard participants used to write their thoughts produced the same effect on thought usage. Experiment 3 demonstrated that thoughts influenced attitudes more when listed while background music was low (vs. high) Pitch can influence attitudes through a meta-cognitive thought reliance process whether emerging from the recipient, channel, or context.
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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 | 0.003 | 0.020 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".