MétaCan
Menu
Back to cohort
Record W6931648760 · doi:10.5683/sp3/sz1lis

Replication Data and Code for: The Canadian Income Taxation: Statistical Analysis and Parametric Estimates

2021· dataset· en· W6931648760 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2021
Typedataset
Languageen
FieldDecision Sciences
TopicReliability and Agreement in Measurement
Canadian institutionsMcMaster University
Fundersnot available
KeywordsReplicateReplication (statistics)Parametric statisticsStatistical analysisCode (set theory)Nonparametric statisticsData file

Abstract

fetched live from OpenAlex

The data and programs replicate tables and figures from "The Canadian Income Taxation: Statistical Analysis and Parametric Estimates ", by Kurnaz and Yip. Please see the ReadMe file for additional details.

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)0.014
metaresearch head score (Gemma)0.121
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 score0.277
Threshold uncertainty score0.928

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.121
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0060.015
Science and technology studies0.0050.002
Scholarly communication0.0040.002
Open science0.0050.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.2770.088

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 head0.202
GPT teacher head0.423
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
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueBorealisSame topicReliability and Agreement in MeasurementFrench-language works237,207