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Record W7135344760

Incoterms and International Taxes

2018· other· W7135344760 on OpenAlexaboutno aff
Michaela Christain

Bibliographic record

VenueIowa State University Digital Repository (Iowa State University) · 2018
Typeother
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsTerminology
DOInot available

Abstract

fetched live from OpenAlex

The business world is becoming increasingly more global. In the global market, shipping terminology is guided by the use of Incoterms. Incoterms are international shipping terminology that allocate the costs, responsibilities, and risks the buyer and the seller must bear during the shipment. Alternatively, in the United States, shipping terminology and sales contracts are based off the Uniform Commercial Code. The purpose of this paper has been to identify current research on the tax implications of Incoterms. The methodology was a literature review of current research and discussions over tax consequences emphasizing international taxes. In an analysis of Canadian indirect taxes, Incoterms can have unwanted tax implications if the appropriate Incoterms is not selected to match the parties’ intentions. Furthermore, more research and discussion should be continued as Incoterms usage will increase as businesses in the United States continue to expand internationally.

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)0.006
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 score0.028
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0030.003
Scholarly communication0.0070.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0210.001

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 head0.008
GPT teacher head0.179
Teacher spread0.172 · 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
Published2018
Admission routes1
Has abstractyes

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