A substantive model of the annual financial reporting exercise in a non‐market corporate
Bibliographic record
Abstract
Purpose – Although it is acknowledged that the dissemination of financial information to stakeholders is a communications process, the main focus of prior research has been on the documents themselves rather than the context in which the information is generated, selected and disseminated. This paper remedies this deficiency by drawing on communication theory to construct a substantive model of the annual financial reporting exercise. Design/methodology/approach – A longitudinal study employing grounded theory was conducted in a non‐market corporate in the U.K. This involved documentary analysis, non‐participant observation and in depth interviews. Findings – The research identified three distinct functions of financial reporting which are formed through the inter‐action of four major determinants: producers' objectives, stakeholders' objectives, the political determinant, the environmental determinant. The level of satisfaction of producers and stakeholders with the perceived function of the annual corporate report leads to an aftermath. This may be either a reinforcement aftermath or it may be a destabilizer aftermath that will necessitate changes in the four determinants. Research limitations/implications – The study was conducted in a non‐market corporate in the UK and caution should be used in attempting to generalize to market corporates. Originality/value – The substantive model offers a diagnostic framework to further explore the nature and dynamics of the annual financial reporting exercise with the evidence of an aftermath being a key finding from the research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".