“Houses still standing” : modernity, myth and memory on Nova Scotia’s Devil’s Island
Bibliographic record
Abstract
Once known as the "singing island" by folklorist Helen Creighton, Nova Scotia's Devil's Island has been sorely neglected by academics.By uncovering its history, mapping the community, and exploring Creighton's role in perpetuating the island's folk identity, this paper will examine the influence of the island on Creighton's later archival work.In exploring the island's shifting identity, from the epitome of true folk to an abandoned ghost village, this paper will also show how both identities promoted by Creighton contribute to her manufactured idea of the folk, which was later exploited by the tourism sector.This study also examines the effects of the relocation during WWII on former residents, exploring their inability to move back to the island after the war.With the recent passing of many former residents, "an intimate fund of memory" has disappeared and Devil's Island has become what Pierre Nora refers to as a lieu de mémoire.Using interviews from former residents and their descendants collected in 1998 and 2021, my paper will examine the disparity between second-hand memory and the childhood nostalgia for a lost place.This paper examines collected memories to highlight how the physical loss of the island contributed to the intense nostalgia and collective longing for a place no longer in existence.Applying both Pierre Nora's theory on the interconnectedness of history and memory and Maurice Halbwachs' theory of collective memory, I will analyze the shared memory and community experienced by former residents even after their displacement.April 9, 2021 Table of Contents Introduction………………………………………………………………………………………3 Chapter One: Helen Creighton and the Folk Identity……………………………………………14 Chapter Two: Community, Loss & Life on Devil's Island……………………………………...27 Chapter Three: Descendants of the Island and the Shifting Collective Memory………………..42 Conclusion……………………………………………………………………………………….53 Bibliography……………………………………………………………………………………..
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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 | 0.010 | 0.011 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".