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Record W7099886350

Executive Summary Smart Social Policy –“Making Work Pay”

2002· article· en· W7099886350 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicProbabilistic and Robust Engineering Design
Canadian institutionsnot available
Fundersnot available
KeywordsEarningsPayrollWork (physics)Punitive damagesProductivityQuarter (Canadian coin)EmployabilityQuality (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

Over the past quarter century, disparities in earnings from employment have widened. The well paid have experienced earnings gains, while market incomes at the low end of the spectrum have stagnated or even declined. Almost two million adult Canadians work for less than $10 an hour – about one in six employed people. These jobs do not pay enough to support a family, yet workers face barriers to advancing their incomes. Workplace barriers occur because employers concentrate more on controlling payroll costs than they do on productivity growth and the development of skills. Public policy barriers occur because the structure of taxes and transfers can create punitive marginal effective tax rates, and the cost of high quality child care far exceeds the budget of lowpaid workers. Low-paid work is concentrated in retail trade, hotel and accommodation services, manufacturing, finance, and personal service industries. The people in these jobs are generally well-educated: 40 percent have completed high school, and 36 percent have a post-secondary diploma or degree. About 35 percent of these jobs are temporary and 36 percent are part-time. About one third of the workers are the only breadwinner in their

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.107
GPT teacher head0.339
Teacher spread0.232 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2002
Admission routes1
Has abstractyes

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