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Record W2272697190

The Output Implications of Higher Labour Force Participation

2003· preprint· en· W2272697190 on OpenAlexaboutno aff
David Gruen, Matthew Garbutt

Bibliographic record

VenueRePEc: Research Papers in Economics · 2003
Typepreprint
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsDemographic economicsQuarter (Canadian coin)PercentileFalling (accident)CommonwealthEconomicsDistribution (mathematics)Educational attainmentGovernment (linguistics)Labour economicsPolitical scienceDemographyGeographyEconomic growthSociologyPsychology
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the output implications of a significant rise in Australian labour force participation over the next forty years. Using the projections in the Commonwealth Government’s 2002-03 Intergenerational Report as a benchmark, it generates alternative projections assuming that, for each age-and-gender cohort, Australian participation rates rise gradually over (roughly) the next twenty years to reach the 80th percentile of the distribution of current participation rates across the OECD. Over the following twenty years, it assumes that Australian participation rates remain at these higher values. These alternative projections, if they were realised, would imply gradually rising aggregate labour force participation in Australia for most of the next twenty years, rather than gradually falling participation, as projected in the Intergenerational Report. Output in twenty years time would be about 9 per cent higher than that projected in the Intergenerational Report, and would remain about 9 per cent higher for the following twenty years. About one-third of the rise in output in these alternative projections would be accounted for by higher participation by 45-64 year old males, and between one-sixth and one-quarter by higher participation by people aged 65 and over. Some of the rise in participation rates in the alternative projections could occur as a consequence of recent rises in educational attainment flowing through to older age groups over time. Much of the rise, were it to occur, would need to come about as a consequence of changes in policy and in community attitudes, particularly to older workers.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.103
GPT teacher head0.446
Teacher spread0.343 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations21
Published2003
Admission routes1
Has abstractyes

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