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Record W2245951236

Using Accounting Reform to Stimulate Sustainability Practices in Higher Education: A Sociological Analysis of Financial Storytelling

2011· article· en· W2245951236 on OpenAlexaff
Stephen G. Kerr, Elizabth A Lange

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsSustainabilityStorytellingBusinessAgency (philosophy)Process (computing)AccountingSustainable developmentAccounting managementFinanceSociologyPolitical scienceAccounting information systemSocial scienceNarrative
DOInot available

Abstract

fetched live from OpenAlex

University communities are interested in adopting sustainable practices; however, sustainable values often come into conflict with financial reports. In fact, sometimes financial reports show that sustainable values are inefficient. This paper explores financial reports as an economic language based upon the agency relationship that exists between investors and organizational managers. We give specific examples that illustrate how sustainable institutions of higher learning are held back because of these boundaries. Several suggestions are given as to how sustainable values can be integrated into the process of financial reporting. A goal of a sustainable community can be more easily achieved if it works with, rather than against, the underlying relationship that forms the current systems that are used to tell our financial stories.

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)0.007
metaresearch head score (Gemma)0.015
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0110.023
Scholarly communication0.0090.010
Open science0.0010.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.060
GPT teacher head0.303
Teacher spread0.243 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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