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Record W1609447734 · doi:10.1080/00031305.2015.1033985

Advanced Placement Statistics: Expanding the Scope of Statistics Education

2015· article· en· W1609447734 on OpenAlexaboutno aff
Allan J. Rossman, Roy T. St. Laurent, Josh Tabor

Bibliographic record

VenueThe American Statistician · 2015
Typearticle
Languageen
FieldMathematics
TopicStatistics Education and Methodologies
Canadian institutionsnot available
Fundersnot available
KeywordsStatisticsStatistics educationScope (computer science)Quarter (Canadian coin)Descriptive statisticsSummary statisticsMathematics educationComputer sciencePsychologyMathematicsGeography

Abstract

fetched live from OpenAlex

A list of consequential developments in the field of statistics for the past quarter-century must include the creation and implementation of the Advanced Placement (AP) program in Statistics. This program has introduced millions of high school students to our discipline over the past 18 years, contributing to the large increase in the number of undergraduate students pursuing statistics as their major in college. ASA members and leaders have played a substantial role in shaping this program and furthering its success.

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)0.064
metaresearch head score (Gemma)0.166
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.337

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0640.166
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0130.010
Science and technology studies0.0020.006
Scholarly communication0.0090.017
Open science0.0040.012
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0470.026

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 head0.171
GPT teacher head0.466
Teacher spread0.295 · 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
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

Citations9
Published2015
Admission routes1
Has abstractyes

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