Hidden wisdom or pseudo-profound bullshit? The effect of speaker admirability
Bibliographic record
Abstract
How do people reason in response to ambiguous messages shared by admirable individuals? Using behavioral markers and self-report questionnaires, in two experiments (N = 571) we examined the influence of speakers’ admirability on meaning-seeking and wise reasoning in response to pseudo-profound bullshit. In both studies, statements that sounded superficially impressive but lacked intent to communicate meaning generated meaning-seeking, but only when delivered by high admirability speakers (e.g., the Dalai Lama) as compared to low admirability speakers (e.g., Kim Kardashian). The effect of speakers’ admirability on meaning-seeking was unique to pseudo-profound bullshit statements and was absent for mundane (Study 1) and motivational (Study 2) statements. In Study 2, participants also engaged in wiser reasoning for pseudo-profound bullshit (vs. motivational) statements and did more so when speakers were high in admirability. These effects occurred independently of the amount of time spent on statements or the complexity of participants’ reflections. It appears that pseudo-profound bullshit can promote epistemic reflection and certain aspects of wisdom, when associated with an admirable speaker.
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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 | 0.006 | 0.052 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 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".