Accounting at Mahou, brewers, from the 1890s to 1970s
Bibliographic record
Abstract
Extant accounting history literature contains some research of accounting on breweries. This research is useful in understanding the evolution of accounting practices within firms (i.e. management accounting) over time, as brewing has been a rather ubiquitous practice of humankind. Breweries also preserve their past, resulting in useful archival sources to study the evolution of business practices (including accounting). However, much of the research has been in an Anglo-Saxon context, which limits its usefulness and comparative international accounting histories are lacking. Breweries, many of whom have survived for centuries, operated in differing political, legal, professional, and economic contexts. This, in turn affects how accounting is practiced within (and without) breweries. Some of the extant literature adopts strands of institutional theory to explore the stability/change of brewery accounting, and this study follows suit. The brewing business studied here is Mahou, a Spanish business, which operated in a non-Anglo-Saxon context. The objective of this paper is thus to explore how internal accounting practices were affected by a differing institutional context. Available accounting records of Mahou reveal stable practices over a period of about 80 years, despite much change in its operating context. It also reveals an emphasis on meeting legal requirements, with little evidence of accounting for decision-making.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".