MétaCan
Menu
Back to cohort
Record W1486561322 · doi:10.3386/w14647

Social Security Programs and Retirement Around the World: The Relationship to Youth Employment, Introduction and Summary

2009· report· en· W1486561322 on OpenAlexaff
Jonathan Gruber, Kevin Milligan, David A. Wise

Bibliographic record

VenueNational Bureau of Economic Research · 2009
Typereport
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSocial securityPolitical scienceDemographic economicsLabour economicsSociologyEconomic growthEconomicsLaw

Abstract

fetched live from OpenAlex

This is the introduction and summary to the fourth phase of an ongoing project on Social Security Programs and Retirement Around the World.The first phase described the retirement incentives inherent in plan provisions and documented the strong relationship across countries between social security incentives to retire and the proportion of older persons out of the labor force.The second phase documented the large effects that changing plan provisions would have on the labor force participation of older workers.The third phase demonstrated the consequent fiscal implications that extending labor force participation would have on net program costs-reducing government social security benefit payments and increasing government tax revenues.This volume presents the results of analyses of the relationship between the labor force participation of older persons and the labor force participation of younger persons in twelve countries.Why countries introduced plan provisions that encouraged older persons to leave the labor force is unclear.After the fact, it is now often claimed that these provisions were introduced to provide more jobs for the young, assuming that fewer older persons in the labor force would open up more job opportunities for the young.Now, the same reasoning is often used to argue against efforts in the same countries to reduce or eliminate the incentives for older persons to leave the labor force, claiming that the consequent increase in the employment of older person would reduce the employment of younger persons.The validity of such claims is addressed in this volume.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.002

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 head0.636
GPT teacher head0.579
Teacher spread0.056 · 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

Citations47
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueNational Bureau of Economic ResearchSame topicRetirement, Disability, and EmploymentFrench-language works237,207