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Record W4408384500 · doi:10.1111/1911-3838.12395

Wildfire Guardians and the Complexity of Not‐for‐Profit Accounting*

2025· article· en· W4408384500 on OpenAlexaffvenueabout
Michael J. Marin, Elisa Zuliani

Bibliographic record

VenueAccounting Perspectives · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBusinessAccountingProfit (economics)EconomicsMicroeconomics

Abstract

fetched live from OpenAlex

Abstract The Wildfire Guardians (WG) case presents students with management accounting and financial reporting issues related to a not‐for‐profit (NFP) organization dedicated to managing and reducing the severity of wildfires in Canada. The case situates students in the role of the newly appointed CFO, who is tasked with analyzing WG's accounting issues, assessing the financial implications of a new strategic opportunity, and making recommendations that could shape the organization's future. By engaging with this case, students will gain insights into real‐world challenges and dilemmas faced by NFP organizations and will sharpen their skills in fund accounting, financial decision‐making, and the application of accounting standards for NFP organizations.

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)0.011
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0110.035
Scholarly communication0.0170.010
Open science0.0010.005
Research integrity0.0030.005
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 head0.035
GPT teacher head0.287
Teacher spread0.252 · 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 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

Citations0
Published2025
Admission routes3
Has abstractyes

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