Bibliographic record
Abstract
Abstract Maybe Christianity is actually true. Maybe it is what believers say it is. But at least two problems make the thoughtful person hesitate. First, there are so many other options. How could one possibly make one’s way through them to anything like a rational and confident conclusion? Second, why do so many people choose to be Christian in the face of so many reasons not to be Christian? Yes, many people grow up in Christian homes and in societies, but many more do not. Yet Christianity has become the most popular religion in the world. Why? This book begins by taking on the initial challenge as it outlines a process: how to think about religion in a responsible way, rather than settling for such soft vagaries as “faith” and “feeling.” It then clears away a number of misunderstandings from the basic story of the Christian religion, misunderstandings that combine to domesticate this startling narrative and thus to repel reasonable people who might otherwise be intrigued. The second half of the book looks at Christian commitment positively and negatively. Why do two billion people find this religion to be persuasive, thus making it the most popular “explanation of everything” in human history? At the same time, how does Christianity respond to the fact that so many people find it utterly implausible, especially because of its narrow insistence on “just one way to God,” and because of the problem of evil that seems to undercut everything it asserts? Grounded in scholarship but never ponderous, Can I Believe? takes on the hard questions as it welcomes the intelligent inquirer to give Christianity at least one good look.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.085 | 0.051 |
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".