Bibliographic record
Abstract
In a recent paper, José Ángel Gascón extends the Frankfurtian notion of bullshit to the sphere of argumentation. On Frankfurt’s view, the hallmark of bullshit is a lack of concern for the truth of an utterance on the part of the bullshitter. Similarly, Gascón argues, the hallmark of argumentative bullshit should be viewed as a lack of concern for whether the reasons that are adduced for a claim genuinely support that claim. Gascón deserves credit for drawing attention to the idea of argumentative bullshit. Nevertheless, we argue, his treatment leaves room for further refinement as he fails to clarify important points and misidentifies several features of argumentative bullshit. In particular, Gascón’s account fails to accommodate non-Frankfurtian forms of argumentative bullshit. This paper aims to amend and extend his proposal and proposes a general account that can encompass both Frankfurtian and non-Frankfurtian forms of argumentative bullshit.
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 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 | 0.019 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.041 |
| Scholarly communication | 0.011 | 0.029 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".