"The Intentional Fallacy" Reconsidered LA RECONNAISSANCE DE ''L'AFFECTIVE INTENTIONNELLE''
Bibliographic record
Abstract
People easily confuse the terms of “the intentional fallacy” and “the affective fallacy.” I think when W. K. Wimsatt and Monroe C. Beardsley fi rst introduced the two terms, what they wanted to stress was priority of the work as the basis of critical judgment. In our process of literary analyzing, I think the author, the work, and the reader are a trinity hardly separable. The work is only an “extention” where the author’s intention and the reader’s meet. Still we must agree that insofar as communication is possible, there should be a considerable amount of sameness remaining between the author’s intention and the reader’s through the medium of the “extention”. Key words : The intentional fallacy; The affective fallacy; Intention; Extention; Objectivity Resume Les gens confondent facilement les termes de “l’affective intentionnelle’’ et ‘‘le sophisme affective.” Je pense que lorsque WK Wimsatt et Monroe C. Beardsley introduit les deux termes, ce qu’ils voulaient souligner etaient la priorite du travail comme la base d’un jugement critique . Dans notre processus d’analyse litteraire, je pense que l’auteur, le travail, et le lecteur sont un peu separable trinite. Le travail n’est qu’une ‘‘extension” ou l’intention de l’auteur et le lecteur de repondre. Cependant, nous devons convenir que dans la mesure ou la communication est possible, il devrait y avoir une quantite considerable de la memete restant entre l’intention de l'auteur et le lecteur de par l’intermediaire de la «extension». Mots cles : Affective intentionnelle; Sophisme affective; Intention; Extension; L’Objectivite
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.072 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 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".