Bibliographic record
Abstract
Debate over how the working class movement should fight the global restructuring of capital is of crucial importance for the Left. For this reason, Errol Black’s critique (in C&C 46) of my article, ‘Beyond Nationalism, Beyond Protectionism: Labour and the Canada-US Free Trade Agree-ment ’ (C&C 43, 1991) is to be welcomed. Unfortunately, Black’s comment fails to come to terms with the central flaws in the nationalist politics which have dominated the Left and the labour movement in English-speaking Canada. Indeed, the lapses and confusions in his article confirm the most important arguments I sought to make. Here I will touch on four points which are of special importance. First, Black uncritically echoes the view that it is the bilateral free trade agreement (BFTA) which has produced attacks on social spending and workers ’ living standards. He writes that ‘with the integration of the two markets, Canada would be under relentless pressure to harmonise tax, social welfare, labour relations, etc., policies with those of the US.’ To attribute these phenomena to a trade deal, rather than the McNally argues that there are major flaws in the nationalist politics dominating the Left in English Canada which succeed in dividing the working class movement at a critical time and divert attention from the real issues.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.072 | 0.019 |
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".