Treacherous Ascents: On Seeking Common Ground for Conflict Resolution
Bibliographic record
Abstract
The judgment competent reasoners exhibit in deciding when reasoning should not be used to resolve disagreements is eroded by adopting the popular strategy of ascending to higher levels of generality. That strategy encourages disputants to believeoften incorrectly-that they stand on some common ground that can be exploited to reach agreement. But if we regularly assume that we share values and interests with our opponents in seemingly intractable disputes, we risk losing the ability to judge whether or not we share enough. And when we lose track of the difference between promising and unpromising conditions for reasoning, we end up trying to reason at the wrong times. Such reasoning can in turn seriously damage our reasoning skills themselves.
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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 | 0.034 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.057 |
| Scholarly communication | 0.014 | 0.028 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 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".