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Record W3097241435

COVID-19: Child Care Tax Provisions in H.R. 7327 [July 24, 2020]

2020· article· en· W3097241435 on OpenAlexaboutno aff
Conor F. Boyle, Molly F. Sherlock, Margot L. Crandall-Hollick

Bibliographic record

VenueLibrary of Congress. Congressional Research Service · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsChild careQuarter (Canadian coin)PandemicCoronavirus disease 2019 (COVID-19)CARE ActFamily medicineBusinessMedicinePolitical scienceEconomic growthHealth careEconomicsGeographyDiseaseInfectious disease (medical specialty)
DOInot available

Abstract

fetched live from OpenAlex

From the Document: The Coronavirus Disease (COVID-19) pandemic has broadly impacted child care in the United States Surveys conducted in April of both working families with young children and child care providers found that the majority of child care providers had fully closed or reduced their enrollment Data from the Bureau of Labor Statistics suggest that the number of child care workers decreased by about one-third between March and April [ ] and about one-quarter between March and June, with the latter number potentially reflecting the effects of states partially reopening Parents and providers have questions about if and when child care facilities will be able to reopen safely The COVID-19 pandemic has also amplified concerns about child care affordability As Congress continues to debate whether more needs to be done to address child care at the federal level, the House Rules Committee recently reported a resolution that would allow the House to consider two bills related to child care One of those bills, the Child Care for Economic Recovery Act (H R 7327), includes several tax provisions, as summarized in this Insight Child care--Taxation;Economics;Disaster recovery

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)0.007
metaresearch head score (Gemma)0.012
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.250
Threshold uncertainty score0.497

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0060.002
Scholarly communication0.0080.002
Open science0.0040.004
Research integrity0.0260.013
Insufficient payload (model declined to judge)0.0360.031

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 head0.065
GPT teacher head0.372
Teacher spread0.307 · 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
Published2020
Admission routes1
Has abstractyes

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Same venueLibrary of Congress. Congressional Research ServiceSame topicGender, Labor, and Family DynamicsFrench-language works237,207