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Record W2135094284

Labour Market Seasonality in Canada: Trends and Policy Implications

2005· article· en· W2135094284 on OpenAlexaboutno aff
Andrew Sharpe, Jeremy Smith

Bibliographic record

VenueCSLS Research Reports · 2005
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSeasonalityUnemploymentEconomicsSeasonal adjustmentDemographic economicsLabour economicsEconomic growthVariable (mathematics)Ecology
DOInot available

Abstract

fetched live from OpenAlex

The objective of this paper is to examine labour market seasonality in Canada over the past three decades in order to shed light on what policies might be best suited to address seasonal economies. The main findings are as follows. The seasonality of the Canadian economy has declined since 1976 according to a wide range of output and labour market variables. However, since 1996 unemployment rate seasonality has increased. Seasonality ?both in employment and the unemployment rate ?is much higher for the young than for older workers and much higher for men than for women. Canada’s level of employment seasonality was more than three times higher than that in the United States in 2003. However, unemployment rate seasonality was perhaps surprisingly the same in the two countries. Relative to OECD countries, Canada has average unemployment rate seasonality, but very high employment seasonality. Atlantic Canada has higher levels of employment and unemployment rate seasonality than the other provinces reflecting a greater importance of primary industries and greater propensity of employers to hire part-year workers. Seasonal unemployment represents a much more important public policy issue than seasonal employment. The basic problem is an underlying lack of employment opportunities in rural and remote areas where seasonal unemployment is concentrated, not seasonal unemployment itself. An economic development strategy that ensures that all persons who want full year work can obtain it must be the most important element in any attempt to reduce seasonal unemployment. But such a strategy might need to be supplemented, at least in the short-to-medium term, by out-migration, particularly in very high unemployment regions, and incentives for firms to transform seasonal work into full-year work, or at least into near full-year work. Since unrestricted benefits for seasonal EI repeaters will not reduce seasonal unemployment, a strong case can be made that long-term income support for the seasonally unemployed is not in the long-run in the best interest of the beneficiaries, high unemployment regions, and the country, although reducing such benefits is politically difficult.

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.494

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.012
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.141
GPT teacher head0.517
Teacher spread0.376 · 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

Citations11
Published2005
Admission routes1
Has abstractyes

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