Educators Responding to Rapid Demographic Change in New Brunswick: “It is not Inclusion if They Are Just Sitting in the Desk”
Bibliographic record
Abstract
New Brunswick has experienced a decline in population in recent years. Successive governments are attempting to increase its population through various population and economic strategies, including immigration. Our research investigates how New Brunswick educators and school leaders are responding to the demographic changes in their schools and communities. Guided by constructivist epistemology, we analyzed qualitative data (i.e. surveys, focus group and individual interviews, public policy and school documentation, and extensive field notes) from case studies in two New Brunswick high schools in neighboring communities that confronted rapid demographic change the past five years. Six main themes were constructed from the data sources we analyzed. The themes are further described and relate to: Educational Challenges; Stress and Anxiety; The School Environment; The Education System; Sustainable Professional Development; and Fostering Positive Relationships. From these themes, we construct several suggestions for better pedagogical and leadership practices in demographically changing schools in New Brunswick. As New Brunswick continues to welcome people from all over the world, it is imperative that educators, school leaders, public policy-makers, and community members work closely and collaboratively to support population and economic growth in all sectors, and ensure all new Canadians feel welcome and a sense of belonging within the province. Key words: New Brunswick, Immigration, Demographic Change, Diversity, Intercultural Leadership, Citizenship Education, Social Justice, Social Action La population du Nouveau-Brunswick a connu un déclin au cours des dernières années. Les gouvernements successifs tentent d'augmenter sa population par diverses stratégies démographiques et économiques, dont l'immigration. Notre recherche examine la réaction des éducateurs et des dirigeants scolaires du Nouveau-Brunswick aux changements démographiques dans leurs écoles et leurs communautés. Guidés par l'épistémologie constructiviste, nous avons analysé des données qualitatives (c'est-à-dire des sondages, des entretiens individuels et de groupe, de la documentation sur les politiques publiques et les écoles, et des notes détaillées prises sur le terrain) provenant d'études de cas dans deux écoles secondaires du Nouveau-Brunswick situées dans des communautés voisines qui ont été confrontées à un changement démographique rapide au cours des cinq dernières années. Six thèmes principaux ont été construits à partir des sources de données que nous avons analysées. Les thèmes sont décrits plus en détail et se rapportent aux sujets suivants : Les défis éducatifs ; le stress et l'anxiété ; l'environnement scolaire ; le système éducatif ; le développement professionnel durable ; et la promotion de relations positives. À partir de ces thèmes, nous élaborons plusieurs suggestions pour améliorer les pratiques pédagogiques et de leadership dans les écoles du Nouveau-Brunswick qui connaissent des changements démographiques. Comme le Nouveau-Brunswick continue d'accueillir des gens de partout dans le monde, il est impératif que les enseignants, les dirigeants scolaires, les décideurs publics et les membres de la communauté travaillent en étroite collaboration pour soutenir la croissance démographique et économique dans tous les secteurs, et pour s'assurer que tous les nouveaux Canadiens se sentent bienvenus et ont un sentiment d'appartenance à la province. Mots-clés: Nouveau-Brunswick, immigration, changement démographique, diversité, leadership interculturel, éducation à la citoyenneté, justice sociale, action sociale
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".