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Record W7096651963

Norteamérica. Revista Académica del CISAN- UNAM

2016· article· en· W7096651963 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicPsychology Research and Bibliometrics
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationLatin AmericansPoliticsGermanEuropean unionPrincipal (computer security)
DOInot available

Abstract

fetched live from OpenAlex

How to cite Complete issue More information about this article Journal's homepage in redalyc.org Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative The future of continental cooperation within North America remains uncertain. However, if the three principal countries of this continent intend to deepen the ties that have brought them together under the NorthAmerican Free TradeAgree-ment, they will need to navigate the process of further international accords, both in terms of treaties and negotiated changes to domestic laws. An important but overlooked feature of this process is the fact that each of the three countries has a federal system different from that of the others in terms of relative overall institu-tional strength and degrees of centralization and decentralization. Like the European Union (particularly in relation to the German federal system and the principle of subsidiarity), the North American countries will need to take federal-ism into account when negotiating and implementing any future legal agreements and institutions among themselves. A strongly centralized federal system with a weak institutional presence can facilitate the negotiation and imposition of new legal arrangements that will provide for further economic and political coopera-tion. However, a more strongly decentralized system with a strong overall insti-tutional presence (resembling the Canadian model) could potentially provide the impetus for more effective implementation of these legal agreements as well as foster a greater sense of acceptance and involvement in a broader NorthAmerican community among regions and local communities.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.182
Threshold uncertainty score0.609

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.007
Science and technology studies0.0010.002
Scholarly communication0.0070.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1820.107

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 head0.081
GPT teacher head0.417
Teacher spread0.335 · 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
Published2016
Admission routes1
Has abstractyes

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Same topicPsychology Research and BibliometricsFrench-language works237,207