Bibliographic record
Abstract
This chapter argues that the relationship between tradition and change can be illuminated through a better understanding of how tradition is (re)produced. How do traditions emerge, how do appeals to tradition serve to justify decisions, and, in what ways does justifying a choice in terms of tradition exercises a constraint over the kind of decision that can be made? The first part of the chapter discusses Patrick Glenn's approach to these questions, as seen, for example, in his claim that tradition is 'massaged', always entails change, and cannot control its own boundaries. It then goes on to put his ideas to the test by examining a controversial Rabbinical innovation recorded in the Talmud; Hillel's introduction of the 'Prozbul' so as to secure loans that would otherwise have been cancelled each sabbatical year. A meta-analysis of how this institution has since been categorized by those within and outside the Talmudic tradition suggests that successful innovation depends on the ability of interpreters to convince the relevant audience(s) that it embodies the best efforts to continue the tradition. It concludes that anachronism may be the price we need to pay if fidelity to tradition is to be more than antiquarianism.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".