Bibliographic record
Abstract
Abstract This paper argues that bullshit is a practical resource for self‐deceiving individuals, or those who merely prefer to avoid self‐examination, insofar as it is able to provide a mask for poor doxastic hygiene. While self‐deception and bullshit are distinct phenomena, and bullshit does not cause self‐deception, bullshit disrupts the capacity to interrogate the motivational biasses that fuel deception. The communicative misdirection engaged in by ordinary social bullshitters is applied reflexively by the self‐deceiver to distort, evade, and obfuscate the self‐deceiver's self‐accounting. This discussion presupposes a broadly narrative approach to self‐awareness and discusses how a motivated susceptibility to bullshit offers an explanation how our reports about ourselves can be frequently at odds with reality, and suggests that a complacency about rational validation of belief outside of self‐certainty, i.e., the prevalence of bullshit, is even more of a threat than Frankfurt thought it to be.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".