Bibliographic record
Abstract
In Willing, Wanting, Waiting, Richard Holton lays out a detailed account of resolutions, arguing that they enable agents to resist temptation. Holton claims that temptation often leads to inappropriate shifts in judgment, and that resolutions are a special kind of first- and second-order intention pair that blocks such judgment shift. In this paper, I elaborate upon an intuitive but underdeveloped objection to Holton’s view—namely, that his view does not enable agents to successfully block the transmission of temptation in the way that he claims, because the second-order intention is as equally susceptible to temptation as the first-order intention alone would be. I appeal to independently compelling principles—principles that Holton should accept, because they help fill an important explanatory gap in his account—to demonstrate why this objection succeeds. This argument both shows us where Holton’s view goes wrong and points us to the kind of solu-tion we need. In conclusion, I sketch an alternative account of resolutions as a first-order intention paired with a second-order desire. I argue that my account is not susceptible to the same objection because a temptation that cannot be blocked by an intention can be blocked by a desire.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.033 |
| Scholarly communication | 0.011 | 0.024 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".