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Record W3081448766 · doi:10.2308/jeta-2020-052

Teaching Blockchain to Accounting Students

2020· article· en· W3081448766 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

VenueJournal of Emerging Technologies in Accounting · 2020
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBlockchainComputer scienceStorytellingHash functionAccountingKnowledge managementNarrativeBusinessComputer security

Abstract

fetched live from OpenAlex

ABSTRACT The objective of these teaching notes is to provide an outline for offering blockchain related foundational knowledge to accounting students so they can evaluate and prepare for the effect of blockchain on the accounting profession. The approach is driven by the following principle: Given that accounting students do not want to become programmers or cryptographers, what is the essential blockchain knowledge that they need to know? Based on my own teaching and research experience, I propose and explain how I use a combination of storytelling and scaffolding approach to focus on the delivery of the following topics: (1) why study blockchain? (2) general foundational knowledge (i.e., element of complete transactions and double spending), (3) interactive exercises to explain technical knowledge on topics such as hashing and proof-of-work (mining), and (4) blockchain implementation in a supply chain setting.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0050.002
Research integrity0.0000.001
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 head0.016
GPT teacher head0.293
Teacher spread0.277 · 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