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Record W4401812804 · doi:10.55016/ojs/sppp.v16i1.77426

Energy Transition Under the New NAFTA: Challenges in the Critical Minerals Supply Chain

2023· article· en· W4401812804 on OpenAlexfundaboutno aff
John P. Hayes, Alem Cherinet

Bibliographic record

VenueThe School of Public Policy Publications · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsnot available
FundersGlobal Affairs Canada
KeywordsSupply chainEnergy transitionBusinessMedicine

Abstract

fetched live from OpenAlex

Demand for critical minerals, battery metals, and the nearshoring of electric vehicle (EV) manufacturing have implications for all trading partners of the updated North American Free Trade Agreement, now called the United States-Mexico-Canada Agreement (USMCA). North American EV manufacturing is driven by initiatives such as the battery belt in the US and Canada’s commitment to clean technology. Mexico, as a major auto-component manufacturer and producer of critical minerals, holds a significant role in supporting the regional supply chain. However, recent developments in Mexican natural resource policy, including the nationalization of lithium deposits and exploration moratoriums, present challenges for foreign miners operating in Mexico, including the risk of future limited participation in the mining sector. Canadian miners hold a dominant role in Mexican mineral exploration, and Mexico is Canada’s third-largest trading partner. The political landscape in Mexico, with the ruling Morena party controlling both the national government and majority of state governments, further complicates the situation. Policy changes in 2023 to the mining sector’s regulatory requirements are the most significant reforms to the sector since the early 1990s. The reforms are in response to prominent, long-standing grievances from various non-industry stakeholders and seek to mitigate against future negative social and environmental impacts of mining. The reforms include shorter mining concession permits, stricter environmental impact assessments, and new permitting procedures on water use.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.964
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.109
GPT teacher head0.291
Teacher spread0.182 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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 routes2
Has abstractyes

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