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Record W7016243841

Who's In Who's Out: A Look at Access to Employer-based Retirement Plans and Participation in the States

2016· dataset· en· W7016243841 on OpenAlexaboutno aff

Bibliographic record

VenueIssue Lab (Candid) · 2016
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsWorryAsideRetirement ageQuarter (Canadian coin)Retirement communitySocial securityWork (physics)Retirement planningMandatory retirement
DOInot available

Abstract

fetched live from OpenAlex

With the aging of the nation's population, a continuing decline in the availability of traditional pensions, and concerns about the future of Social Security, many workers in the United States worry that they won't have enough money set aside for their retirements. The Employee Benefit Research Institute's 2014 annual Retirement Confidence Survey found that only 22 percent of Americans are very confident that they will have enough money for a comfortable retirement, while 36 percent are somewhat confident. Twenty-four percent are not at all confident.In addressing these concerns, policymakers have emphasized the need to expand access to what are known as employer-sponsored defined contribution plans, such as 401(k)s. The ability of employees to contribute directly from their paychecks and the use of features such as automatic enrollment make the workplace an effective place to encourage saving. These employer-sponsored plans are how Americans now accumulate the vast majority of their private retirement funds, but large gaps in coverage exist.Today, only about half of workers participate in a workplace retirement plan, according to an analysis of data compiled by The Pew Charitable Trusts. Overall, 58 percent of workers have access to a plan, while 49 percent participate in one. Looking at the numbers a different way, more than 30 million full-time, full-year private-sector workers ages 18 to 64 lack access to an employer-based retirement plan.To help more people save for their later years, lawmakers in Congress have introduced retirement savings initiatives. Separately, President Barack Obama unveiled his "myRA" program in 2014 with a similar goal. As of Nov. 4, 2015, people without retirement plans can sign up to save through myRA. States are also acting to increase retirement savings. Lawmakers in more than half of the states have introduced measures to either create or study state-sponsored retirement savings plans for employees who don't have access to such a plan in the workplace. Illinois, for instance, established the Secure Choice Savings Program, which will start enrolling certain workers in new payroll-deduction retirement accounts by 2017. Washington state has created a marketplace in which small employers and the self-employed can shop for retirement plans.

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)0.002
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: Observational
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.089
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0030.004
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.000

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 head0.045
GPT teacher head0.362
Teacher spread0.318 · 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
GenreDataset

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
Published2016
Admission routes1
Has abstractyes

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