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Record W6927545002 · doi:10.3278/6004672w019

All dressed up and nowhere to go: PIAAC in Canada

2018· other· en· W6927545002 on OpenAlexaboutno aff

Bibliographic record

VenueSocial Science Open Access Repository (GESIS – Leibniz Institute for the Social Sciences) · 2018
Typeother
Languageen
FieldMedicine
TopicActinomycetales infections and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracySample (material)Field (mathematics)Adult literacyWork (physics)Public policyTrend analysisSurvey data collectionOrder (exchange)

Abstract

fetched live from OpenAlex

The international adult literacy survey series has been conducted for over 25 years, culminating most recently in the PIAAC results released in 2013. Canada was deeply involved in the development of the series, and for PIAAC funded a sample size around seven times the average. Yet the analysis of the results has been limited, and impact on the field yet more so. This chapter discusses one explanation for the failure of the survey to have a wider impact, and identifies implications for adult education policy more broadly.

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)0.005
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: Other · Consensus signal: Other
Teacher disagreement score0.084
Threshold uncertainty score0.613

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.007
Science and technology studies0.0100.002
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0160.002

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 head0.071
GPT teacher head0.417
Teacher spread0.346 · 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
GenreOther

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
Published2018
Admission routes1
Has abstractyes

Explore more

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