Bibliographic record
Abstract
espanolEste trabajo ofrece una presentacion general del perfil personal y de la filosofia de Bernard Lonergan (teologo y filosofo catolico canadiense), en especial de su teoria cognitiva y su epistemologia. Se centra en la exposicion de sus ideas a partir de su obra filosofica mas importante: Insight: A Study of Human Understanding (Londres 1957, edicion critica: Toronto 1992). Para exponer la filosofia del conocer de Lonergan, se tratan los puntos siguientes: 1. Vida; 2. Influencia; 3. Obras; 4. Exposicion general de la filosofia de Lonergan; 5. El conocer como objeto de la filosofia; 6. La auto-apropiacion como meta y como metodo de la filosofia; 7. Cuestiones filosoficas fundamentales y jerarquia de las distintas areas filosoficas; 8. La teoria cognitiva y la cuestion cognitiva: a. El metodo empirico generalizado; b. La estructura dinamica del conocer (experimentar, entender, juzgar); 9. La epistemologia y la cuestion epistemologica: a. La finalidad del conocer; b. La nocion de objetividad; 10. La metafisica del sujeto del conocer y la cuestion metafisica: a. La nocion de ser (realidad); b. El deseo infinito de conocer y de ser un autentico conocedor. EnglishThe paper gives a general presentation of the profile and philosophical achievements of Canadian Catholic theologian and philosopher Bernard Lonergan, especially his cognitional theory and epistemology. It confines itself to expounding his views from his main philosophical book: Insight: A Study of Human Understanding (London 1957, the critical edition: Toronto 1992). To present Lonergan's philosophy of knowing it addresses the following issues: 1. Life; 2. Influence; 3. Works; 4. A general account of Lonergan's philosophy; 5. Knowing as a subject of philosophy; 6. Self-appropriation as the aim and method of philosophy; 7. Basic philosophical questions and a hierarchy of the areas of philosophy; 8. Cognitional theory and the cognitional question: a. The generalized empirical method; b. The dynamic structure of knowing (experiencing, understanding, judging); 9. Epistemology and the epistemological question: a. The aim of knowing; b. The notion of objectivity; 10. The metaphysics of the knowing subject and the metaphysical question: a. The notion of being (reality); b. The infinite desire to know and being an authentic knower
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".