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Record W2604373331 · doi:10.4000/etudesecossaises.1154

Highlanders and Maritimers in Alistair MacLeod’s “Clearances”

2017· article· en· W2604373331 on OpenAlexaffabout
André Dodeman

Bibliographic record

VenueÉtudes écossaises · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicScottish History and National Identity
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsHistory

Abstract

fetched live from OpenAlex

This paper examines how Canadian writer Alistair MacLeod, in his latest short story entitled “Clearances”, attempts to reconnect the twentieth-century maritime culture of Cape Breton, Canada, to an idealized Scottish past that dates back to the eighteenth-century clearances of the Highlands. Along with No Great Mischief, the only novel he published in his lifetime, his short stories tackle the themes of displacement, forced migration and collective memory. After focusing on the role played by the Atlantic Ocean in his short stories as a reminder of historical and cultural displacement, this study will explore how MacLeod’s “Clearances” reconstructs a forgotten line of filiation between Cape Breton and the Highlands that sends characters and readers back and forth in time. MacLeod’s purpose to emphasize the prime importance of local culture is twofold: his stories not only serve to resist oblivion, they also express a refusal to surrender to the powerful pressures of a present-day process of globalization that challenges and threatens the survival of local identities.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.401

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0400.035
Scholarly communication0.0100.005
Open science0.0010.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.050
GPT teacher head0.259
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2017
Admission routes2
Has abstractyes

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