Bibliographic record
Abstract
In this chapter, James Tully takes us deep into the phenomenology of the kind of dialogue across traditions that is capable of disrupting the unjust power structures that currently connect diverse traditions in the modern global order. He contrasts “genuine dialogue,” in which traditions have equal status as forms of human understanding, with the many kinds of “false dialogue” that are likely to emerge under circumstances of unequal power and power-knowledge. As beings that make sense of the world through our received traditions, we tend to project onto others the terms that make the world meaningful to us. Deparochializing our political thought must begin by “reparochializing” it, recognizing that the truths we hold to be self-evident have arisen within a sociohistorically specific context. The “deep listening” required for genuine dialogue requires practices of the self that must be cultivated over time before dialogue can generate reciprocal elucidation and transformation. When we succeed, participants in this dialogue can achieve not only mutual understanding but also the possibility of bringing to light ways of “thinking, judging, deliberating, and acting together in response to the situation they share that were unimaginable and unthinkable prior to the dialogue.”
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".