Bibliographic record
Abstract
Abstract No single issue dominated economic discourse within the Empire-Commonwealth more than the question of imperial preference: the proposal that all members abandon free trade (where they adhered to it) and by various means grant tariff preferences to one another better than those given to most favoured nation status foreign trading partners. The issue often dominated political discourse and although the UK did not adopt preference before 1914, preferential tariffs were introduced in many dominions, something enabled by UK treaty abrogations. The clash of ideas between free traders, empire free traders, protectionists, and preferentialists, dominated successive congresses of chambers of commerce. This chapter uses these clashes to reconstruct the pan-Empire-Commonwealth dimensions of the great tariff reform debate through successive decades. It highlights in particular the crucial role played by Canadian preferentialists in advancing the issue, the way in which the debate connected across the empire, and the ways in which a focus on chamber highlights the divisions within as well as between political units within the Empire-Commonwealth. It reconstructs the debates, offering unique quantitative as well as qualitative measures. It charts how the political realities of the Empire-Commonwealth, as well as economic interests, shaped positions (stymying Empire Free Trade in particular). Overall it shows how chambers as a whole drifted towards an advocacy of imperial preference.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.056 | 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".