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Record W3169950416 · doi:10.1111/1911-3838.12263

<scp>OneFeather</scp> Mobile Wallet: A Digital Solution for Indigenous Peoples in Canada?<sup>*</sup>

2021· article· en· W3169950416 on OpenAlexaffvenueabout
Kin Lo, Fiana Liu, Johnson Chao-Sheng Huang

Bibliographic record

VenueAccounting Perspectives · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIndigenousProduct (mathematics)Mobile paymentBusinessFoundation (evidence)CommercePolitical scienceFinanceLawPaymentMathematics

Abstract

fetched live from OpenAlex

ABSTRACT OneFeather is a real company located in British Columbia. The company aims to provide much‐needed services to Indigenous peoples, specifically those in Canada. This case involves a proposed digital wallet specifically designed for the needs of Indigenous peoples in Canada. Students are tasked to consider how the digital wallet needs to consider the unique circumstances of Indigenous peoples, the applicable tax laws, the appropriate technological foundation for the product, and strategies to roll out the product and attract users.

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.

How this classification was reachedexpand

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.015
GPT teacher head0.290
Teacher spread0.275 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2021
Admission routes3
Has abstractyes

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