Bibliographic record
Abstract
If we have no idea what God [would be], then what sense is there in asking whether God exists or not? (Peterson et al. 1991, p. 49) EXISTENCE AND ESSENCE QUESTIONS This book would be about God, that is, it is about God, supposing This One exists. But since this book would be about God, it is appropriate to begin by saying something about what this book would be about. For, to say it would be about God is not so much to say as to advert or point. ‘God’, after all, is a proper name. And it is for proper names to name, not to describe. Generally we have descriptions in mind when we use names, but people can, when they converse, have in mind different descriptions. And although this need not make trouble for the identifying functions of names, since different descriptions can pick out the same things, it does mean that communication is uncertain when the existence of things that people would speak of with a name is at issue. People, when they use names, generally intend to name things, but they do not always succeed, and when it is a question whether a name does name, it becomes important to discussion that there be a shared understanding of the character of what it would name.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".