Bibliographic record
Abstract
Some years ago, I ran into a former colleague and ex-Dean. He was now a judge. After some friendly banter, he commented that he had recently read a piece that I had published about the hoary problem of ‘state action’ in constitutional law; it argued that the persisting doctrinal dilemmas were attributable to the contradictions of the underlying liberal basis of rights-talk. He had reason to read it, he said, because he had to decide a case that raised related problems about the institutional reach of Canada’s Charter of Rights. However, after he had generously complimented me on the piece, he made a familiar complaint – ‘For all the force of your critique, you never tell us what we should do. Don’t you think that you should tip your hand and give us a sense of what we should decide?’ I simply responded with my customary shrug and by saying that ‘I’m not in the business of judging – that’s your challenge, not mine’. His implicit sense of what academics do and should do was very different to my own. In this short essay, I want to explain what is the ‘business’ that I think that I am in as an academic or, more grandly, as an intellectual. In particular, I will explore and explain what the implications of these intellectual commitments are for the fraught and misunderstood relationship between the academic and judicial (and, by implication, the professional) sectors of the legal community. In order to do this, I will first of all introduce an important distinction between the two different types of intellectual role – a traditional one and a critical one – that polarize law schools; this duality is far from original or unfamiliar. Then, I will take the recent confirmation process of Elena Kagan in her appointment to the United States Supreme Court to illustrate the political characteristics and institutional context which give rise to and sustain the pervasive acceptance by most law professors of their role as traditional intellectuals. Lastly, I will look at how this continuing nexus between judges and law professors affects academics in the way that they go about doing their intellectual business. Throughout the essay, I will emphasise that ‘law is politics’ and that there is no site of political innocence or independence that academics or judges can inhabit in meeting their professional roles and responsibilities.
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 | 0.061 | 0.134 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.042 | 0.082 |
| Scholarly communication | 0.064 | 0.024 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.021 | 0.027 |
| Insufficient payload (model declined to judge) | 0.008 | 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".