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Record W2297885878

Comparing Public and Private Compensation in British Columbia

2013· article· en· W2297885878 on OpenAlexaffabout
Amela Karabegović, Jason Clemens

Bibliographic record

VenueSSRN Electronic Journal · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsFraser Institute
Fundersnot available
KeywordsPublic sectorPrivate sectorPensionWageLabour economicsBusinessGovernment (linguistics)EconomicsDemographic economicsFinanceEconomic growthEconomy
DOInot available

Abstract

fetched live from OpenAlex

As British Columbia’s provincial government continues to struggle with both deficits and finding ways to constrain spending, there is heightened interest in how wages and non-wage benefits (compensation) in the public sector compare with those in the private sector. While a lack of non-wage benefits data mean that there is insufficient information to make a definitive statement about total compensation between the private and public sectors, the data that are available indicate that the public sector enjoys a clear wage premium. There are also strong indications that the public sector has more generous non-wage benefits than the private sector. After controlling for such factors as gender, age, marital status, education, tenure, size of firm, type of job, and industry, public sector workers (including federal, provincial, and local) located in British Columbia in April 2011 enjoyed, on average, a 13.6 percent wage premium over their private sector counterparts. When unionization is factored in, the premium is reduced to 11.2 percent. As of 2011, 89.8 percent of public sector workers in British Columbia were covered by a registered pension compared to 19.4 percent of private sector workers. In addition, 95.6 percent of British Columbia’s public sector workers who were covered by a pension enjoyed a defined benefit pension plan compared to 49.3 percent of private sector workers. In 2011, job losses were greater in B.C.’s private sector than in the public sector: 4.3 percent of private sector workers lost their jobs compared to 0.6 percent of public sector 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 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)0.006
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 score0.049
Threshold uncertainty score0.354

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.008
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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
Published2013
Admission routes2
Has abstractyes

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