The Globalization of Guinness: Marketing Taste, Transferring Technology
Bibliographic record
Abstract
Abstract Brewed in 50 countries and consumed in 150, Guinness Stout has become a global commodity. Although associated with Irish pubs and diasporic populations, it has also become popular in former British colonies of Africa and Southeast Asia. This article adopts a mobility studies perspective to show how Guinness built its global appeal, first through trade and settlement in the British empire during the nineteenth and early twentieth centuries, and subsequently by navigating the upheavals of decolonization and economic integration in the second half of the twentieth and early twenty first centuries. Transfers of brewing technology and marketing techniques were essential for the company’s success in postcolonial markets. In particular, this article shows that metropolitan exporters could work with colonial subjects to subvert imperial policies. Such alliances were not entirely unexpected, for with its headquarters in a former British colony, Guinness was ideally situated to blend the global and the local, just as the company had successfully bridged the bloody divide of Irish independence, remaining as beloved in Belfast, loyalist heartland of Northern Ireland, as in Dublin, capital of the Irish Republic.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
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".