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Geopolitics of Assessment

2018· other· en· W2922832536 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

VenueThe TESOL Encyclopedia of English Language Teaching · 2018
Typeother
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsQueen's University
Fundersnot available
KeywordsGeopoliticsTest of English as a Foreign LanguageLanguage assessmentContext (archaeology)Test (biology)Dimension (graph theory)Power (physics)Political scienceLiteracyLanguage proficiencySpace (punctuation)English languagePoliticsLinguisticsSociologyMathematics educationPedagogyPsychologyHistoryLaw

Abstract

fetched live from OpenAlex

English as an international language (EIL) refers to the use of English as a means by which people from different parts of the world communicate with each other. Geopolitics concerns political power within and across geographic space. Within this broadly defined EIL context, this entry frames the political power of assessment and addresses this power from two dimensions. The first dimension is the geopolitics of international language testing, which deals with the testing of proficiency in English by speakers of other languages whose purpose of taking the test is to pursue academic study in English‐speaking countries, such as the Test of English as a Foreign Language (TOEFL) and the International English Language Testing System (IELTS). The second dimension focuses on the testing of proficiency in English by speakers of other languages whose purpose is for schooling in English‐speaking countries, such as the Ontario Secondary School Literacy Test (OSSLT) in Canada and the No Child Left Behind (NCLB) policy in the United States.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.694
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.020
GPT teacher head0.410
Teacher spread0.390 · 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