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Record W2312774039 · doi:10.18192/olbiwp.v4i0.1106

Multidimensionality of assessment in the Common European Framework of Reference for languages (CEFR)

2012· article· en· W2312774039 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

VenueOLBI Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPerspective (graphical)Context (archaeology)Process (computing)Raising (metalworking)Domain (mathematical analysis)Computer sciencePsychologyLinguisticsArtificial intelligenceGeographyEngineering

Abstract

fetched live from OpenAlex

This article intends to discuss complexity of assessment by presenting its several layers and dimensions as they are conceptualized in the Common European Framework of Reference for languages (CEFR) and to show how the CEFR advocates an inclusive vision of assessment able to integrate several perspectives. After presenting the CEFR perspective of the nature and role of assessment, the article investigates some challenges practitioners are facing and their needs as to the assessment process. It also aims at casting light on the actual and potential impact of the CEFR on assessment cultures in different contexts. The data presented in this article, collected within the ECEP (Encouraging the Culture of Evaluation among Professionals) project of the Council of Europe and within its extension in the Canadian context, will help to understand why the CEFR can be seen as a relevant awareness-raising tool in the domain of assessment and beyond.

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)0.004
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 score0.091
Threshold uncertainty score0.147

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.073
GPT teacher head0.445
Teacher spread0.371 · 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