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Record W6976304028 · doi:10.6068/dp14baa36993b34

Trend 1991 - 2007. Statistics Canada. CANSIM: Education, Training and Learning - Adult Education and Training | Country: Canada | Province: Saskatchewan | Table: Registered apprenticeship training, registrations by major trade groups and sex | Variable: Building construction trades, Both sexes | Units: #, 1991-2007. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-067.

2015· other· en· W6976304028 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2015
Typeother
Languageen
FieldComputer Science
TopicSpreadsheets and End-User Computing
Canadian institutionsnot available
Fundersnot available
KeywordsCensusStatistics educationApprenticeshipAdult educationDescriptive statisticsTraining (meteorology)Economic statisticsSocioeconomic statusOfficial statistics

Abstract

fetched live from OpenAlex

Statistics Canada (2015). CANSIM: Education, Training and Learning - Adult Education and Training | Country: Canada | Province: Saskatchewan | Table: Registered apprenticeship training, registrations by major trade groups and sex | Variable: Building construction trades, Both sexes | Units: #, 1991-2007. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 075-001-067. Dataset: Presents statistics on adult education in Canada. Adult education is defined as education received after the initial cycle of full-time formal education, which begins in childhood. CANSIM is Statistics Canada's key socioeconomic database. The datasets included here provide statistics on the Canadian population, and the nation’s resources, economy, society, and culture. In addition to conducting a Census every five years, approximately 350 active surveys are conducted on virtually all aspects of Canadian life. Statistics are provided for the nation as a whole, provinces, and other subnational geographies where available. Category: Education Source: Statistics Canada Established as Canada's central statistical office by the Statistics Act of 1985, Statistics Canada is required to "collect, compile, analyse, abstract and publish statistical information relating to the commercial, industrial, financial, social, economic and general activities and conditions of the people of Canada." Its main objectives are to provide statistical information and analysis about Canada’s economic and social structure and to promote sound statistical standards and practices. http://www.statcan.gc.ca/ Subject: Continuing Education, Adult Education

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)0.002
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.101
Threshold uncertainty score0.475

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0100.049
Science and technology studies0.0040.001
Scholarly communication0.0050.003
Open science0.0060.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1010.063

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 head0.027
GPT teacher head0.248
Teacher spread0.221 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2015
Admission routes1
Has abstractyes

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