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Record W3208243166

West Coast Equestrian Association (WCEA) – The Fraud

2014· article· en· W3208243166 on OpenAlexaffabout
Doug Kalesnikoff, Suresh Kalagnanam, Vince Bruni‐Bossio

Bibliographic record

VenueSSRN Electronic Journal · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRevenueCorporate governanceControl (management)Association (psychology)AccountingRecreationPublic relationsBusinessAction (physics)Political scienceManagementPsychologyFinanceLawEconomics
DOInot available

Abstract

fetched live from OpenAlex

West Coast Equestrian Association (WCEA) is a blend of two real situations and the organization is disguised but based on a similar organization that one of the authors advised on governance issues. The similar organization has been in existence for 35 years to support equestrian sport and recreation in a Western Canadian city. The situation depicted in the case is that WCEA is in a crisis situation after it is discovered that the Executive Director has fraudulently absconded with potentially hundreds of thousands of dollars. The focus of the fraud is on the revenue side where multiple sources of revenue exist and a significant portion of the receipts are in cash. The case can be used in senior undergraduate or graduate courses focusing on management control systems, internal controls, assurance or forensic accounting. The student is required to assume the role of an accountant being asked by the chair of the Board of Directors to determine how much money might be missing. This computation requires the student to estimate the expected revenue from each source and compare the estimated amount to the actual amount reported in the financial statements. Next, students are asked to identify the management control issues existing in the organization, using Merchant and Van der Stede’s framework of results control, action controls, personnel controls and cultural controls. Finally the case requires students to discuss whether the Board could be found to be negligent in fulfilling its duties. A previous but very similar version of the case was successfully used in a graduate accounting course on assurance; students rated the case positively on a number of different dimensions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.126
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.003
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0300.004

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 head0.010
GPT teacher head0.193
Teacher spread0.183 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2014
Admission routes2
Has abstractyes

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Same venueSSRN Electronic JournalSame topicSports Analytics and PerformanceFrench-language works237,207