MétaCan
Menu
Back to cohort
Record W2809631190 · doi:10.29007/ctcq

Local Patterns of National Household Survey Non-Response in Canadian Cities

2018· paratext· en· W2809631190 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

VenueEasyChair preprint · 2018
Typeparatext
Languageen
FieldMathematics
TopicCensus and Population Estimation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCensusGeographyUnit (ring theory)American Community SurveyGovernment (linguistics)Ethnic groupData collectionSurvey data collectionOfficial statisticsRegional scienceDemographyPolitical scienceStatisticsSociologyPopulationPsychologySocial science

Abstract

fetched live from OpenAlex

Statistics Canada and the Canadian government invoked a dramatic change in the collection of detailed demographic and other data for the Census year 2011. Despite reverting in 2016 to the traditional “long form” census format, the National Household Survey (NHS) of 2011 represents an important and meaningful opportunity for study. Furthermore, with a 10-year gap between instances of the more reliable “long form” survey format, users of detailed census data products face challenges if interested in demographic, economic, social, and other changes that happened between 2006 and 2016 or trends in such data over a period that includes the 2011 NHS. Here we examine patterns of non-response, using the variable Global Non-Response (GNR) in several Canadian cities using dissemination areas (DA) as the unit of analysis. We will also show patterns of similarity and dissimilarity with GNR and other NHS variables (social, demographic, ethnic, housing, etc.).

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.096
GPT teacher head0.344
Teacher spread0.248 · 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