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Record W3047674918 · doi:10.14738/abr.87.8770

The Impact of COVID-19 on the Canadian Economy

2020· article· en· W3047674918 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueArchives of Business Research · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsUniversity of TorontoLaurentian University
Fundersnot available
KeywordsIndex (typography)RecreationCoronavirus disease 2019 (COVID-19)TourismUnemploymentEconomicsAccommodationLabour economicsPandemicDemographic economicsEntertainmentUnemployment rateBusinessEconomic growthGeography

Abstract

fetched live from OpenAlex

This paper examines various types of effects of COVID-19 on Canadian businesses and industrial sectors. Using the data from Labour Force Surveys, the paper explores the impact of COVID-19 on the Canadian labour market. The paper also investigates the relationship between the intensity of lockdown measures ( stringency index) and the unemployment rate for Canada and selected countries. The main findings are the following: 1)The businesses which faced a high level of decreases in demand are food &accommodation,  arts, entertainment, and recreation and retail trade; 2) Small businesses witnessed a higher level of decrease in demand compared to large businesses;  3) The goods- producing industries, especially motor vehicle and parts producing industries experienced the steepest decline in growth rates; 4)The pandemic adversely affected the jobs of women, workers with high school education,  and young workers; 5) Finally, it appears that there is a weak positive relationship between the Stringency Index and the unemployment rate across selected countries including Canada.

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.

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)0.002
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.593
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.193
GPT teacher head0.363
Teacher spread0.170 · 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