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Record W2186758012

Aboriginal Peoples Survey, 2012: Concepts and Methods Guide

2014· article· en· W2186758012 on OpenAlexaboutno aff
Elisabeth Cloutier, Éric Langlet

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsMetisGeographyWork (physics)SocioeconomicsIndigenousEconomic growthSociologyEcologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

The Aboriginal Peoples Survey (APS) is a national survey on the social and economic conditions of First Nations people living off reserve, Metis and Inuit aged 6 years and over. The objectives of the APS are to identify the needs of these Aboriginal groups and to inform policy and programs aimed at improving the well-being of Aboriginal peoples. The APS has been conducted by Statistics Canada since 1991, providing a range of social and economic indicators about Aboriginal peoples. This cycle of the APS was conducted from February 6, 2012 to July 30, 2012. Over 50,000 people were selected to participate in the survey and the final response rate was 76 per cent. The survey design allowed for the production of reliable data for each of the provinces and territories (Atlantic provinces grouped), as well as for each of the four Inuit regions: Nunatsiavut (Northern coastal Labrador), Nunavik (Northern Quebec), the territory of Nunavut and the Inuvialuit region of the Northwest Territories. The survey also targeted four particular education groups: current school attendees in grades one to six; current school attendees in grades seven to 12; high school completers (including equivalency); and high school leavers. This guide is intended to provide a detailed review of the 2012 APS with respect to its subject matter and methodological approaches. It is designed to assist APS data users by serving as a guide to the concepts and measures of the survey as well as the technical details of the survey's design, field work and data processing. The guide is meant to provide users with helpful information on how to use and interpret survey results. The discussion on data quality also allows users to review the strengths and limitations of the data for their particular needs.

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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.522
Teacher spread0.474 · 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 teacher head, not a consensus.

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

Citations44
Published2014
Admission routes1
Has abstractyes

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