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Record W4405500717 · doi:10.1108/oxan-db291727

Ottawa hopes critical mineral output will aid US ties

2024· article· en· W4405500717 on OpenAlexaboutno aff

Bibliographic record

VenueEmerald expert briefings · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCabinet (room)TariffLiberian dollarUs dollarInternational tradePolitical scienceBusinessEconomicsGeographyFinanceExchange rate

Abstract

fetched live from OpenAlex

Significance The challenge of responding to President-elect Donald Trump’s threat of 25% tariffs on Canadian exports has already opened rifts between Ottawa and provincial premiers, as well as within Prime Minister Justin Trudeau’s cabinet, over export taxes involving critical minerals. Impacts In response to Trump’s tariff threats, the Canadian dollar hit a four-year low, potentially boosting margins for Canada’s producers. Trump’s threat of 100% tariffs on BRICS members could disrupt mineral trading, with Brazil and South Africa most affected. Beijing is curbing US-bound critical minerals shipments to prevent transshipment via an extra-territoriality clause that may affect Canada.

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)0.002
metaresearch head score (Gemma)0.008
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: Other · Consensus signal: none
Teacher disagreement score0.097
Threshold uncertainty score0.374

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0140.004
Scholarly communication0.0100.003
Open science0.0010.003
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0970.012

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 head0.020
GPT teacher head0.312
Teacher spread0.292 · 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
Published2024
Admission routes1
Has abstractyes

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