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Record W2603182665

Interstate Shipment of Municipal Solid Waste: 2004 Update

2004· article· en· W2603182665 on OpenAlexaboutno aff
James E. McCarthy

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsnot available
Fundersnot available
KeywordsMunicipal solid wasteWaste managementBusinessEnvironmental scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

This report, which replaces CRS Report RL31051, provides updated information on interstate shipment of municipal solid waste (MSW).Since the late 1980s, Congress has considered, but not enacted, numerous bills that would allow states to impose restrictions on interstate waste shipments, a step the Constitution prohibits in the absence of congressional authorization.Over this period, there has been a continuing interest in knowing how much waste is being shipped across state lines for disposal, and what states might be affected by proposed legislation.This report provides data useful in addressing these questions.Total interstate waste shipments continue to rise due to the closure of older local landfills and the increasing consolidation of the waste management industry.About 35 million tons of municipal solid waste crossed state lines for disposal in 2001, an increase of 9.4% over 2000.Waste imports have grown each year since CRS began tracking them in the early 1990s, and now represent 21.6% of all municipal solid waste disposed at landfills and waste combustion facilities.In the last eight years, reported imports have increased 141%.Pennsylvania remains, by far, the largest waste importer.The state received 10.7 million tons of municipal solid waste and 1.9 million tons of other nonhazardous waste from out of state in 2001, more than 30% of the national total for interstate shipments.Virginia, the second largest importer, received 4.1 million tons, 62% less than the amount received by Pennsylvania.Michigan, the third largest importer, imported 3.6 million tons of MSW in fiscal year 2001; waste imports to Michigan have doubled since 1999.Twenty-three states had increased imports in the current report -the largest increases occurring in Pennsylvania and Michigan.In all, eight states reported imports that exceeded one million tons.While waste imports increased overall, several states (including New Hampshire, South Carolina, Connecticut, Arizona, and Washington) reported sharp declines in waste imports.New York remains the largest exporter of waste, with New Jersey and Illinois in second and third place, respectively.Four states (New York, New Jersey, Illinois, and Maryland) account for more than half the national total of waste exports. 1 Legislation on interstate shipment of waste has been introduced in every Congress since the 100 th .In the 104 th Congress, the Senate passed S. 534.The bill would have granted states authority to restrict new shipments of municipal solid waste from out of state, if requested by an affected local government.In the 103 rd Congress, both the House and Senate passed interstate waste legislation (H.R. 4779 and S. 2345), but lack of agreement on common language prevented enactment.For a discussion of the issues addressed in these bills, see CRS Report RS20106, Interstate Waste Transport: Legislative Issues. 2 This report replaces Interstate Shipment of Municipal Solid Waste: 2001 Update, CRS Report RL31051.Earlier reports, now out of print but available directly from the author, were Interstate Shipment of Municipal Solid Waste: 2000 Update, CRS Report RL30409,

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.142
Threshold uncertainty score0.282

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0130.017
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0160.013

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 head0.010
GPT teacher head0.175
Teacher spread0.165 · 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 designObservational
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

Citations12
Published2004
Admission routes1
Has abstractyes

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