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Record W3046538170 · doi:10.1111/emip.12382

Synergy and Tension between Large‐Scale and Classroom Assessment: International Trends

2020· article· en· W3046538170 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

VenueEducational Measurement Issues and Practice · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsQueen's UniversityBrock University
Fundersnot available
KeywordsScale (ratio)Test (biology)Political scienceMathematics educationPedagogySociologyPsychologyGeographyGeologyCartography

Abstract

fetched live from OpenAlex

Abstract The synergy, or lack thereof, between large‐scale and classroom assessment has been fiercely debated in both academic and policy spheres for decades around the world. This paper seeks to explicate how different countries are utilizing large‐scale testing and test results at the classroom level. Through country profiles, this paper analyzes contemporary developments on the tensions and synergies between large‐scale assessment and classroom teaching, learning, and assessment observed across seven international jurisdictions: United States, Canada, Australia, England, Germany, Finland, and Singapore. The paper concludes with an analysis of international trends leading to a synthesis of root causes contributing to the current limited uptake of large‐scale assessment results at classroom levels.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.096
GPT teacher head0.421
Teacher spread0.324 · 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