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Record W4408405734 · doi:10.33596/coll.130

Collaboration for Cultural Revitalization: Researching the Songs and Stories of Early 20th-Century Woods Workers in Newfoundland and Labrador, Canada

2025· article· en· W4408405734 on OpenAlexaboutno aff
Meghan Forsyth, Ursula A. Kelly

Bibliographic record

VenueCollaborations A Journal of Community-Based Research and Practice · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsArchaeologyGeographyHistoryEthnology

Abstract

fetched live from OpenAlex

This paper provides an account of the interrelated collaborations that emerged as part of an interdisciplinary research project designed to document and revitalize the occupational songs and stories of early 20th-century woods workers in Newfoundland and Labrador, Canada. In the context of a paucity of research related to these industries and occupations and their cultural legacies, we approached the songs and stories not only as cultural and musical texts but also as specific social histories and embedded literacy practices. Our purpose was to identify, primarily through archival research and textual analysis, the extent of this song and story tradition and what it revealed about those at its centre. We then determined ways to reframe and represent this tradition to contemporary audiences interested in the intersections of history, culture, and identity through story and song. The ten-year multi-faceted project unfolded organically through a series of university-community collaborations that spawned communities of practice in Newfoundland, Labrador, and Scotland. In this paper, we explore the nuances of these multi-tiered collaborations, the intersecting and diverging goals and needs that informed them, and the insights and benefits that accrued throughout their duration.

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)0.008
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.097
GPT teacher head0.423
Teacher spread0.326 · 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 designQualitative
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCollaborations A Journal of Community-Based Research and PracticeSame topicCanadian Identity and HistoryFrench-language works237,207