Ecological food practices and identity performance on Cape Breton Island
Bibliographic record
Abstract
As globalization disrupts traditional industries and economies, investigations of localized responses to these disruptions can offer insights to guide strategies in regions facing similar challenges. Cape Breton Island, Nova Scotia, is one such location. Traditionally, the island’s economy was resource based and centred on fishing and coal mining, but tourism became increasingly important in the twentieth century to offset de-industrialization and unemployment. Agriculture has always contributed to the island’s economy but has been concentrated in particular regions with many communities relying on imported foods. In the twenty-first century, global movements for local and ecological food practices have encouraged renewed interest and involvement in food production across Cape Breton. The island’s economic challenges remain significant and government and business leaders responding to unemployment and outmigration have identified tourism and agriculture as areas for expansion. Using a critical ethnographic approach, this study examines Cape Breton’s ecological food movement as a cultural practice through which participants—producers, farmers’ market vendors, consumers, restaurateurs—produce local distinction and perform their identities (Beagan, Power, and Chapman 2015; Johnston, Szabo, and Rodney 2011, Pilgeram 2012, Slocum 2007). Ecological food initiatives raise critical questions of access, labour, cultural identification, and power relations; however, I argue that local, ecological food practices also present opportunities. The collaborative efforts of multiple stakeholders can foster relationships and enrich cultural autonomy within rural communities, illuminating possibilities for building local economies, protecting local environments, and enacting meaningful individual and collective identities (Glowacki-Dudka, Murray, and Isaacs 2012, Sims 2009, Tiemann 2008)).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".