Review of the Canadian English Language Proficiency Index Program (CELPIP)
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.
Bibliographic record
Abstract
The Canadian English Language Proficiency Index Program (CELPIP) is a computer-delivered test for English language proficiency, primarily used for Canadian immigration purposes. This review begins by contextualizing the test’s use as an immigration gatekeeping instrument, followed by an overview of its underlying construct and the four test components: listening, reading, writing, and speaking. We then appraise the test in terms of its accessibility, reliability, validity, authenticity, and impact. While we appreciate the “Canadian-ness” of the test, the user-friendly computer-based test delivery, and the accessible approach to sharing scoring criteria, we also identify several shortcomings regarding transparency in scoring, attention to interactional competence, and attention to research on test impact. We close with a brief commentary on the use of such tests for selecting and controlling immigrants.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it