MétaCan
Menu
Back to cohort
Record W2048559269 · doi:10.1506/wyaw-jlgf-xu60-e8cq

JIT Adoption: The Effects of LIFO Reserves and Financial Reporting and Tax Incentives*

2004· article· en· W2048559269 on OpenAlex
Michael Kinney, William F. Wempe

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueContemporary Accounting Research · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsnot available
Fundersnot available
KeywordsIncentiveBusinessFIFO and LIFO accountingAccrualEarningsEarnings managementAccountingValuation (finance)Monetary economicsDebtFinanceEconomicsMicroeconomics

Abstract

fetched live from OpenAlex

Abstract Using matched samples of JIT adopters and nonadopters, we examine the association of JIT adoption with firms' financial reporting and tax incentives, earnings‐management histories, and LIFO reserve levels. We find evidence that adoption decisions are influenced by the interaction of firms' LIFO reserves with their income smoothing, debt covenant, and tax incentives. We also find that adoption is less likely for firms historically engaging in high degrees of earnings management, particularly when such firms have no substantial LIFO reserves. Our study extends earlier research demonstrating a relation between inventory valuation method and year‐end inventory transactions, and documents a relation between earnings‐management incentives and a fundamental supply‐chain design choice.

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)0.012
metaresearch head score (Gemma)0.043
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.043
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.085
GPT teacher head0.349
Teacher spread0.263 · 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