Markers of Collective Identity in Loyalist and Acadian Speeches of the 1880s: A Comparative Analysis
Bibliographic record
Abstract
This article presents the results of a research project comparing the speeches and sermons of Acadians and descendants of the Saint John Loyalists in the 1880s. At this pivotal moment in New Brunswick history, Loyalist descendants were celebrating a century of survival and progress while Acadians were regrouping after a century of silence. Each group sought to assert its place in a rapidly evolving society. Since neither group could claim for itself a specific geographic territory or a centralized government, a collective identity could be shaped only through the recognition of common values, a shared past, and a collective future. Using text analysis software programs Hyperbase and Sphinx, we explore the lexical worlds by which Loyalist descendants and Acadians expressed their collective identities, and we compare the specific traits and discursive strategies in each of these groups. Resume Cet article presente les resultats d’un projet de recherche qui avait pour objectif de comparer les sermons et discours des Acadiens et des descendants des Loyalistes de Saint-Jean (N.-B.) pendant les annees 1880. Il s’agit d’un moment determinant dans l’histoire des deux peuples; les descendants des Loyalistes commemoraient leur arrivee a Saint-Jean en 1783 et les Acadiens mettaient fin a cent ans de silence collectif par les Conventions nationales acadiennes (1881, 1884 et 1890). Chaque groupe tentait de se forger une place au sein d’une societe en evolution en cette fin de siecle. Cependant, puisque ces groupes sociaux ne pouvaient rattacher leur identite a un territoire officiel ou un gouvernement centralise, leur identite collective reposait fondamentalement sur la reconnaissance de valeurs communes, d’un passe partage et d’un avenir collectif. Par les logiciels d’analyse de donnees textuelles Sphinx et Hyperbase, nous explorons les mondes lexicaux par lesquels les descendants de Loyalistes et les Acadiens exprimaient leur identite collective et nous comparons les traits et les strategies discursives specifiques a chaque groupe.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".