The Failure of the First Illustrative Analogy in Part 3 of David Hume’s Dialogues Concerning Natural Religion
Bibliographic record
Abstract
In Part 2 of David Hume's Dialogues Concerning Natural Religion, Cleanthes puts forth the analogical Argument from Design, the argument intended to establish that the designer of the world possesses an intelligence similar to human intelligence, in light of Cleanthes' claim that the design of the world resembles machines of human contrivance.Philo argues that this argument fails, because the world does not bear a specific resemblance to any type of machine, and, therefore, there is no basis for reasoning analogically to an intelligent cause of design.In Part 3, Cleanthes attempts to strengthen his case through two illustrative analogies: I will examine the first of these-the Articulate Voice speaking from the clouds.Scholarship generally regards the Articulate Voice illustration to fail, precisely because nothing in this illustrative analogy assists Philo in understanding that the world is a machine.My paper/talk reveals that Philo provides additional criticisms of the Articulate Voice illustration in Parts 6 and 7 of the Dialogues, which make Philo's critique even stronger and more enlightening regarding his critical approach to the Design Argument than can be learned from Part 2 alone.
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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.026 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".