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Record W34695440 · doi:10.1016/j.mbs.2021.108720

LAYING OFF EMPLOYEES? WHAT YOU NEED TO KNOW BEFORE PASSING OUT THE PINK SLIPS...

2002· article· en· W34695440 on OpenAlexfundno aff
Edward S. Allen, Rhonda Garman, Charles B. Paterson, Leslie M. Allen, Monica Graveline, N. DeWayne Pope, Annette E. Ball, Alicia M. Harrison, Jerry D. Redmond, David B. Block, Leigh Anne Hodge, Lisa J. Sharp, David R. Boyd, Douglas B. Kauffman, Tod Sloan, William Cobb, Teresa G. Minor, M. Jefferson Starling, Jonathan P. Dyal, Dorman Walker

Bibliographic record

VenueMathematical Biosciences · 2002
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaSimons Foundation
KeywordsLayoffNoticeClosing (real estate)BusinessOvertimeGovernment (linguistics)StatuteWork (physics)Labour economicsUnemploymentLawFinanceEngineeringEconomicsPolitical scienceEconomic growth

Abstract

fetched live from OpenAlex

Unfortunately, recent events and the economy have forced many employers to consider or implement mass layoffs. The Worker Adjustment and Retraining Notification Act (“the WARN Act”) and the Older Workers Benefits Protection Act (“the OWBPA”) are two of the statutes that should be examined before employers implement a reduction in force. The WARN Act: The WARN Act generally requires that employers provide 60 days notice of a “plant closing” or “mass layoff” to affected employees, bargaining representatives, and local government officials. In general, a “plant closing” is a permanent or temporary shutdown of an employment site, facility or operating unit that results in an employment loss to 50 or more employees in any 30-day period. A “mass layoff” is any reduction in force other than a plant closing which, within any 30-day period, results in an employment loss at a single site of employment of either one-third or more of the site’s active employees, but at least 50 employees, or at least 500 employees. Employers that do not employ 100 or more employees, excluding part-time employees, or 100 or more employees who in the aggregate work at least 4,000 hours per week (exclusive of overtime hours), are exempted from the WARN Act’s notice provisions. The WARN Act contains complicated methods of counting employees for determining if an employer is covered by the Act, and for determining if a plant closing or mass layoff has occurred. The WARN Act specifies that certain information be contained in the notices provided to affected employees or their bargaining representatives, and local government officials. If an employer fails to provide the applicable WARN Act notice, employees will be able to recover wages and benefits for the period for which notice was not given. Some employers decide to pay wages and benefits in lieu of providing notice due to productivity and potential workplace violence issues that may arise if employees are provided with 60 days notice of their impending layoff. A civil penalty

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0030.007
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0200.009

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 head0.091
GPT teacher head0.388
Teacher spread0.297 · 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
Published2002
Admission routes1
Has abstractyes

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