MétaCan
Menu
Back to cohort
Record W2074044807 · doi:10.1353/his.0.0008

« Don't I long for Montreal »: L'identité hybride d'une jeune migrante franco-américaine pendant la Première Guerre mondiale

2008· article· en· W2074044807 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHistoire sociale · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsAssociation of Canadian Universities for Northern Studies
Fundersnot available
KeywordsHumanitiesArtSociology

Abstract

fetched live from OpenAlex

Between July 1917 and October 1918, Alma Drouin, a young Franco-American woman from Laconia, New Hampshire, sojourned in Montreal. She had been drawn to Canada's metropolis by the opportunities that it offered for professional mobility, as well as by its big-city attractions. Through an analysis of Alma's correspondence and her diaries, we have attempted to understand the ways in which she represented her daily life in Montreal, along with the place of this big city in her broader mental geography. Alma Drouin possessed a hybrid identity and a transnational consciousness, the latter evident in her participation in a cross-border network of correspondents. Both this network and Alma's use of geographical mobility to achieve social mobility were part of a long migratory tradition in the western world and in French Canada. While Alma constructed herself in her correspondence and her diaries as an independent "working girl", she was nonetheless dependent upon a significant cross-border network of relatives, friends, and acquaintances.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.219
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.227
Teacher spread0.216 · 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