MétaCan
Menu
Back to cohort
Record W7024439688

Social Security Statements: Social Security Administration Should Better Evaluate Whether Workers Understand Their Statements

2005· report· en· W7024439688 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2005
Typereport
Languageen
FieldPhysics and Astronomy
TopicCold Atom Physics and Bose-Einstein Condensates
Canadian institutionsnot available
Fundersnot available
KeywordsSocial securityAdministration (probate law)Government (linguistics)Critical security studiesAccountabilityPaymentFinancial statementPrivate sector
DOInot available

Abstract

fetched live from OpenAlex

A letter report issued by the Government Accountability Office with an abstract that begins "The Social Security Statement is the federal government's main document for communicating with more than 140 million workers about their Social Security benefits. By law, the statement must show an individual's annual earnings, payments into Social Security and Medicare, and projected benefits. The Social Security Administration also uses the statement to explain the various types of Social Security benefits and to encourage greater financial planning for retirement. GAO conducted a review to examine (1) how well recipients understand the current statement, (2) how the Social Security Administration is evaluating the statement's understandability, and (3) the promising practices used by private sector companies and other industrial countries. GAO's information was obtained from its national survey and focus groups of statement recipients, a firm that evaluates benefit statements, officials from three other countries (Canada, Sweden, and the United Kingdom), and other experts from the private sector."

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)0.016
metaresearch head score (Gemma)0.044
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 score0.027
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.044
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0030.004
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0240.009

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 head0.037
GPT teacher head0.268
Teacher spread0.231 · 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
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueUniversity of North Texas Digital Library (University of North Texas)Same topicCold Atom Physics and Bose-Einstein CondensatesFrench-language works237,207