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Record W3117657564

Ontario's Craft Beer Industry: Current Assessment and Future Directions

2016· article· en· W3117657564 on OpenAlexaboutno aff
Natasha Gaudio

Bibliographic record

VenueYork University Digital Library (York University) · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsCraftCurrent (fluid)BusinessEngineeringGeographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The micro-brewing, or craft brewing industry, is a rapidly emerging section of Ontario's economy and local food system (Agriculture & Agri-Food Canada, 2015; Beer Canada, 2016). Since the late 1980s, over 300 breweries have opened shop in Ontario. The growth of the industry is interesting for a number of reasons. The government control of beer and alcohol sales in the province has created a number of challenges for small scale brewers, challenges only now beginning to shift. Historically, the beer industry has been defined by the consolidation of three major industrial scale brewers who control at least 80% of the market. The growing craft sector has pulled local agriculture toward commercial hop production, and opened up discussion of grain sourcing and processing. The trend toward local consumption has created a broader dialogue that questions the dominant corporate and government controlled framework of beer and alcohol sales in Ontario. The industry's recent growth also appears to, in part, be related to the broader local food movement. 
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\nThis paper offers an interdisciplinary discussion on the emerging industry. It relies on three major lenses to offer a current assessment of the industry and the experience a brewing entrepreneur has in Ontario at present. First, it looks at the craft brewing industry within the framework of the local food network in Ontario. Second, this paper places the small to medium enterprise (SME) network of the micro-brewing industry within the framework of the Green Economy, which sees SMEs as having a pivotal role. It also seeks to understand the role of SMEs in contributing to a low-growth, or steady-state economy as outlined by Victor, 2008. Finally, this paper approaches the industry at the individual company level, examining business practices and sustainability therein. The approach taken by this paper is useful in understanding the functional and operational challenges and successes food SMEs have in carrying out their place within the green economy and local food system. 
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\nThis paper contributes a new perspective to the limited existing literature on the craft beer industry in Ontario, and by extension the emerging role of SMEs in the growing local food sector. By undertaking analysis of four distinct breweries of various life-spans and scale, it assumes some common challenges or successes the brewing entrepreneur would find in this sector. The major questions addressed in this paper are: what role do SMEs have to play in the local food movement in Ontario; what are their entrepreneurial limitations or strengths under the current system, and by extension, what are their capabilities in integrating sustainability into their business practices? 
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\nLastly, the findings highlight patterns and trends, and offer some recommendations regarding the future of craft in the Province and some speculations on leveling the playing field of the retail sales channels systems. Results show that craft brewing entrepreneurs are committed to maintaining independence and autonomy over their businesses, are driven by passion for the craft and are mindful of growing their businesses responsibly. Many of these entrepreneurs are highly conscientious and critical of growing too large, and aim to integrate ethics and sustainability into their business practices in response to the glaring issues corporate consolidation has created for themselves and the economy.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.636
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.009
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.175
Teacher spread0.162 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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