Reconstructing Heritage and Cultural Identity in Marginalised and Hinterland Communities: Case Studies from Western Newfoundland
Bibliographic record
Abstract
This essay examines the issue of missing heritage, cultural identity, and regeneration of two historically marginalised communities in the Humber River Basin region of western Newfoundland, Canada: Woods Island and Crow Gulch. This region was shaped by the implementation of international treaties which restricted settlement until the turn of the twentieth century by Britain, France and the United States. The first case study focuses on a former fishing community in the Bay of Islands, Woods Island, whose prosperity once coincided with the need by large fish producers based in Gloucester, Massachusetts; they relied on the Bay of Islands for a herring bait fishery to conduct their operations, making the location one of the most important sources of supply in the North Atlantic. Issues surrounding treaty rights and access to this region’s resources resulted in international arbitration and The Hague Tribunal of 1910, and set a legal precedent for opening up global access to the world’s oceans. A half-century later, in the face of the forces of ‘modernisation’, Woods Island was resettled under pressure from the Newfoundland government, as part of a larger strategy to transform the island’s society and economy. Its heritage remains however important to former residents and their families in understanding a world now lost. The second case study explores an abandoned underclass community, consisting mostly of residents with French/Aboriginal background who were largely discriminated against because of their ethnicity. While also no longer in existence, Crow Gulch in its iconic role is significant in the wake of a recent major Mi’kmaw resurgence in Western Newfoundland. Together, these studies demonstrate how to conserve tangible and intangible culture of marginalised communities by linking micro-history to macro-history and how to preserve the past for future cultural benefit.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".