Bibliographic record
Abstract
P r e f a c eThey say there are benefits to a "perspective from afar."I certainly hope so.I was living in Israel when I first began writing this book.Before that it was Britain and France, making for a total of almost seven years away from Canada.Of course that amount of time and distance can also put one completely out of touch, which is why it is, needless to say, for the reader to judge whether I have suffered that fate here.I sometimes liked to astound Israelis, and Canadians during trips home, by saying that I considered Canadian politics to be more interesting than the Israeli.To be sure, I would say "interesting," not "exciting."What I meant is that, while I'm a political philosopher by trade, the most important issues at stake in Israel still, regrettably, turn largely on matters for which the soldier -and not the thinker -has the greater contribution to make.For a time the peace process changed this somewhat, giving dialogue rather than force a central role.But even then the dialogue enjoined tended to take the form of negotiation rather than conversation, a distinction that plays a central role in the arguments of this book.Put succinctly, when negotiating people struggle to make appropriate trade-offs or compromises in the values or goods at stake, the aim being to bring their conflict to a close by reaching a balanced accommodation.When conversing, however, the goal is to arrive at a shared understanding.This demands something quite difficult
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.562 | 0.413 |
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".