Material, Human, and Social Capital in the Professional Learning Community and Correlations With Teacher/School Characteristics
Bibliographic record
Abstract
This study examines the practices and perceptions of Canadian teachers (N = 172) from the provinces of Québec and New Brunswick with respect to the professional learning community (PLC) in light of several sociodemographic and socioprofessional characteristics of the teachers and those of their school. Factor analyses and correlation tests were thus conducted to determine factor validity and the presence of between-factor connections. The conceptual framework was composed of three groups of predictive factors, namely, material and school-based (material capital), human (human capital), and social (social capital) conditions. This study will enrich the knowledge base on PLCs by describing certain positive and negative correlations and will also contribute to school practices and decisions to prepare and improve the development of Professional learning communities (PLCs) and guide them toward total sustainment. Keywords: Professional learning communities, School environment, Teacher collaboration, PLC teacher beliefs/perceptions, PLC teacher practices Cette étude porte sur les pratiques et les perceptions d’enseignants canadiens (N = 172) provenant du Québec et du Nouveau-Brunswick à l'égard de la communauté d'apprentissage professionnelle (CAP) et ce, en lien avec plusieurs de leurs caractéristiques sociodémographiques et socioprofessionnelles et de celles relatives à leur école. Des analyses factorielles et des tests de corrélation ont été effectués pour examiner la validité factorielle et les liens entre les facteurs. Le cadre conceptuel est composé de trois groupes de facteurs, à savoir les conditions matérielles et institutionnelles (capital matériel), humaines (capital humain) et sociales (capital social). Cette étude enrichit la base de connaissances sur les CAP en décrivant certaines corrélations positives et négatives et contribue également aux pratiques et aux décisions prises dans les écoles afin de préparer et d’améliorer le développement des CAP, et ce, pour amener celles-ci vers la maturité. Mots clés: Communautés d'apprentissage professionnelles (CAP); environnement scolaire; collaboration des enseignants; croyances et perceptions des enseignants; pratiques des enseignants en CAP.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".