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The U.S. Harbor Maintenance Tax: A Bad Idea Whose Time Has Passed?

2007· article· en· W329627820 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTransportation Journal · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicLaw, logistics, and international trade
Canadian institutionsnot available
Fundersnot available
KeywordsContainer (type theory)RevenueEnforcementValue (mathematics)BusinessTax revenueEconomicsCommerceInternational tradeFinancePublic economicsEngineeringLawComputer sciencePolitical science

Abstract

fetched live from OpenAlex

This article presents a critique of the Harbor Maintenance Tax (HMT) as a flawed method of collecting revenues and dispersing benefits. Looking at how it is applied on the Great Lakes of the U.S., a small container of high-value goods is taxed more heavily than an entire shipload of raw material for steel fabrication. It also details legal challenges in recent years, including a decision that exempted exports from the tax, though imports and domestic items are still subject to it. The result has made the HMT inherently unfair, the author argues, since exports put as much demand on harbor facilities as imports and domestic goods. Also, because it is based on a cargo's value, high-value items are steered away from water-borne transport, which is the most fuel efficient under some conditions. Additional objections and criticism are listed, including difficulty in enforcement, suppression of innovation in water-borne transportation, especially on the Great Lakes, forcing container cargo to Canadian ports and problems with how HMT revenues are distributed. Attempts to address many of these flaws are also detailed.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.019
GPT teacher head0.228
Teacher spread0.209 · 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