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Record W4380627315 · doi:10.3138/cpp.2022-009

Job Attributes and Occupational Changes: A Shift-Share Decomposition by Gender and Age Group for Canada, 2006–2016

2023· article· fr· W4380627315 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Public Policy · 2023
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicRegional Economic and Spatial Analysis
Canadian institutionsCenter for Interuniversity Research and Analysis on OrganizationsHEC Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyArt

Abstract

fetched live from OpenAlex

Les changements technologiques ont deux effets de premier ordre sur la nature du travail. Premièrement, les nouvelles technologies peuvent entraîner des changements au sein des professions des personnes sur le marché du travail, et, deuxièmement, elles peuvent pousser ces personnes à passer d’une profession à l’autre. Afin de quantifier ces effets, la présente étude procède à un rapprochement des données détaillées sur les professions tirées des recensements canadiens de 2006 et de 2016 avec des données détaillées qui associent chaque profession à des ensembles de tâches, d’activités et de compétences requises pour cette profession. Les résultats révèlent que l’importance des attributs liés aux interactions sociales et aux tâches cognitives non routinières a augmenté de manière considérable. De plus, la majeure partie de cette augmentation s’est produite au sein de professions étroitement définies. Les hommes ont été plus touchés par les changements observés que les femmes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.649
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.051
GPT teacher head0.245
Teacher spread0.194 · 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