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Record W3186864876 · doi:10.3389/feduc.2021.679972

Analyzing Assessment Practices for Indigenous Students

2021· article· en· W3186864876 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.

Bibliographic record

VenueFrontiers in Education · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of SaskatchewanUniversity of Prince Edward Island
FundersMinistry of Economy, Trade and Industry
KeywordsIndigenousDisadvantageIndigenous educationMeaning (existential)PedagogyFocus groupSociologyPsychologyPolitical scienceAnthropology

Abstract

fetched live from OpenAlex

The purpose of this article is to review common assessment practices for Indigenous students. We start by presenting positionalities—our personal and professional background identities. Then we explain common terms associated with Indigeneity and Indigenous and Western worldviews. We describe the meaning of document analysis, the chosen qualitative research design, and we explicate the delimitations and limitations of the paper. The review of the literature revealed four main themes. First, assessment is subjugated by a Western worldview. Next, many linguistic assessment practices disadvantage Indigenous students, and language-specific and culture-laden standardized tests are often discriminatory. Last, there is a pervasive focus on cognitive assessment. We discuss how to improve assessment for Indigenous students. For example, school divisions and educators need quality professional development and knowledge about hands-on assessment, multiple intelligences, and Western versus Indigenous assessment inconsistencies. Within the past 20 years, assessment tactics for Indigenous students has remained, more or less, the same. We end with a short discussion addressing this point.

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: Empirical
Teacher disagreement score0.721
Threshold uncertainty score0.751

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 communication0.0000.000
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 head0.056
GPT teacher head0.544
Teacher spread0.488 · 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