Bibliographic record
Abstract
Abstract: In this essay, I argue against the bright-line distinction between ideal and nonideal normative political theory, a distinction used to distinguish “stages” of theorizing such that ideal political principles can be deduced and examined before compromises with the flawed political world are made. The distinction took on its familiar form in Rawls and has enjoyed a resurgence of interest in the past few years. I argue that the idea of a categorical distinction — the kind that could allow for a sequencing of stages of theorizing — is misconceived, because wholly “ideal” normative political theory is a conceptual mistake, the equivalent of taking the simplifying models of introductory physics (“frictionless movement in a vacuum”) and trying to develop an ideal theory of aerodynamics. Political organization and justice are about moral friction in the first instance. I examine both logical and epistemological arguments for the position that we need the uniquely idealizing assumptions of ideal theory in order to arrive at, or to know, a genuine theory of justice or political morality; and I find them wanting. Such assumptions as full compliance, consensus, and the publicity principle of universal knowledge about consensus can sometimes be useful, if used carefully and with justification; but they are not categorically different from other idealizing and abstracting assumptions in generating normative theory. What is referred to as “nonideal” theory is all that there is, and it is many kinds of theory, not one — the many ways in which we learn about justice and injustice, and seek to answer questions of practical reason about what ought to be done in our political world.
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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.041 |
| Scholarly communication | 0.008 | 0.018 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".