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Record W7062305600

Trade Adjustment Assistance in Ohio

2012· report· en· W7062305600 on OpenAlexaboutno aff

Bibliographic record

VenueIssue Lab (Candid) · 2012
Typereport
Languageen
FieldDecision Sciences
TopicScientific Measurement and Uncertainty Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsUnemploymentCertificationSubsidyQuarter (Canadian coin)HarmIncome SupportLegislationTaxable income
DOInot available

Abstract

fetched live from OpenAlex

The federal Trade Adjustment Assistance (TAA) program was established to mitigate the economic and personal harm caused by trade-related job loss. During the 2007 recession, Ohio saw record numbers of workers become eligible for the program. In 2011, the second year of the recovery, the number of petitions certified under the program and the number of impacted workers has sharply declined.Eligibility requirements and benefits have varied since the program's enactment in 1974. TAA has generally provided subsidized training, a refundable tax credit for health coverage, case management and some income support to eligible workers who exhaust unemployment insurance benefits. TAA provides more comprehensive support than unemployment compensation and is available for a longer period of time, going beyond even the 99 weeks of unemployment compensation that was available under federal extended UC benefits until earlier this year.Key findingsTAA petitions and certifications, fell in 2011. The number of impacted workers dropped more than 78 percent.Most 2011 petitions cited outsourcing as the cause for TAA coverage.The service sector, which won't be eligible if current TAA rules are allowed to lapse in 2013, accounted for nearly 40 percent of certifications for outsourcing.More than a quarter of all 2011 certifications would be ineligible

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)0.003
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: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0350.002

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 head0.352
GPT teacher head0.438
Teacher spread0.087 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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