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Record W4401812605 · doi:10.55016/ojs/sppp.v16i1.76860

Canada’s New Indo-Pacific Strategy: A Critical Assessment

2023· article· en· W4401812605 on OpenAlexaboutno aff
Hugh Stephens

Bibliographic record

VenueThe School of Public Policy Publications · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsIndo-PacificGeographyBiologyFishery

Abstract

fetched live from OpenAlex

Canada’s Indo Pacific Strategy (IPS), built around five program objectives and funded at CAD$2.3 billion over the initial five year period, has been finally unveiled although details of implementation are generally lacking at present. The strategy lays out an ambitious plan for Canada’s re-engagement with parts of the Indo Pacific region that it has neglected, in relative terms, for a number of years while simultaneously trying to address the challenge of China. The Strategy is a welcome blueprint for diversification of Canadian engagement across various sectors, with ASEAN centrality a key component and closer engagement with North Pacific partners such as Japan and Korea and South Asia, in particular India, constituting core elements, yet the IPS does not close the door on relations with China or propose a decoupling strategy. China is both at the heart of the IPS, and yet not a focus of most of the initiatives. The trade-off for including China in the Strategy seems to have been to vocally demonstrate Canada’s anti-China credentials (to the US and the Canadian public) by talking tough in order to set the stage for more limited forms of ongoing cooperation. This includes calling out Beijing’s activities in a number of areas, including domestic interference in Canadian affairs. There is also a strong infusion of “Canadian values” throughout the document. A risk for Canada is that the Manichean view of China is not shared by many of the countries in the Indo Pacific region that are the targets of the Strategy, and Canada will need to be careful to ensure that strengthening relations with other countries that are targets of the Strategy is based on its own merits and regional priorities and is not portrayed simply as an antidote to expanding Chinese influence. Furthermore, given Canada’s past sporadic engagement with the region it is important that a detailed action plan be put in place quickly. The Trudeau government should be aiming for an “early harvest” for some of the initiatives to avoid the impression of a quick announcement followed by a distinct lag in implementation.

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)0.016
metaresearch head score (Gemma)0.022
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.309
Threshold uncertainty score0.801

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.008
Science and technology studies0.0230.013
Scholarly communication0.0280.010
Open science0.0040.005
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0060.001

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 head0.144
GPT teacher head0.312
Teacher spread0.168 · 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
GenreEmpirical

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
Published2023
Admission routes1
Has abstractyes

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