Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this paper is twofold: to give a good account of the argument from ignorance, with a presumptive argumentation scheme, and to raise issues on the work of Walton, the nature of abduction and the concept of epistemic closure. First, I offer a brief disambiguation of how the terms 'argument from ignorance' and 'argumentum ad ignorantiam' are used. Second, I show how attempts to embellish this form of reasoning by Douglas Walton and A.J. Kreider have been unnecessary and unhelpful. Lastly, I offer a full and effective account of the argument from ignorance and discuss the lessons of the analysis.Le but de cet article est double: donner un bon compte rendu de l'argument par l'ignorance, avec un schème d'argumentation présomptif, et soulever des questions sur certains aspects de l’œuvre de Walton, la nature des raisonnements abductifs et le concept de fermeture épistémique. Premièrement, j'offre une brève désambiguïsation de la façon dont les termes «argument par l'ignorance» et «argumentum ad ignorantiam» sont utilisés. Deuxièmement, je montre comment les tentatives de Douglas Walton et de A.J. Kreider d'embellir cette forme de raisonnement ont été ni nécessaires et ni utiles. Enfin, j'offre un compte-rendu complet et utile de l'argument par l'ignorance et je discute des leçons de l'analyse.
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.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.014 |
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 it