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Record W1620918562 · doi:10.22329/jtl.v4i1.89

An Alternative Vision for Large-scale Assessment in Canada

2006· article· en· W1620918562 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Teaching and Learning · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsBrock University
Fundersnot available
KeywordsScale (ratio)Test (biology)Set (abstract data type)Sample (material)Quality (philosophy)Achievement testEducational assessmentStandardized testPsychologyMathematics educationMedical educationComputer scienceGeographyMedicineCartography

Abstract

fetched live from OpenAlex

Concern over the quality of education has prompted virtually every Canadian province and territory to develop large-scale assessment programs to measure student achievement. The approach of individual provinces and territories varies according to the grades tested, sample size, test format, and frequency of administration. Many provinces also participate in national and international testing programs. This paper provides a general overview of the various large-scale assessment programs across Canada and outlines central arguments for and against student achievement testing. Research documenting the impact of large-scale testing on students and teachers is also reported. The discussion proposes an alternative vision for large-scale assessment aimed at supporting teachers’ instructional practices and student learning. A set of key considerations within this vision serve as a basis for assessment policy reform.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.361
Teacher spread0.349 · 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