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The Imperial Hedge

2025· book-chapter· en· W4413186686 on OpenAlexfundaboutno aff
Preet S. Aulakh

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicIrish and British Studies
Canadian institutionsnot available
FundersYork University
KeywordsHedgeBusinessEconomicsFinancial economicsBiology

Abstract

fetched live from OpenAlex

Abstract Chapter 8 evaluates attempts to resolve the Prince Edward Island’s land question in the late 1860s when the colony contemplated whether to join the Dominion of Canada. In response to the colony’s request for peasant rights, the Imperial Government hedged its bets by taking a two-track route in resolving the Prince Edward Island land question, using inter-colony analogies and decoupling the land question from England. From 1870 to 1872, it first used the Irish Land Act as a model to establish tenant rights in Prince Edward Island when it was uncertain whether the colony would join the Dominion of Canada. Second, after Prince Edward Island joined the Dominion in July 1873, the Imperial Government allowed legislation for the compulsory purchase of large landholdings and absolved itself from its land question on the pretext that the Dominion had the right to resolve land tenure issues based on local considerations under the new governance arrangement.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.033
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0330.004

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.

Opus teacher head0.015
GPT teacher head0.283
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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