Intercultural Research and Education on the Alberta Prairies: Findings from a Doctoral Study
Bibliographic record
Abstract
This article describes a qualitative case study of one high school within a di strict in southern Alberta where increasing numbers of students from diverse cultural, racial, linguistic and socioeconomic backgrounds have entered the school system. Drawing from constructivism and critical theory, the researcher investigated the perceptions of the collective and inclusive leadership elements within the school. Data were coded and categorized using a continuous process of analysis (Stewart, 2007). Dimmock and Walker's (1998, 2005) cross-cultural school focused model supported the researcher in the process of data analysis. Five initial themes arose from the survey instrument and seven major and interrelating themes emerged from the interview data. The seven major themes that emerged in the study were: (a) language and communication barriers; (b) professional development and collaboration; (c) curriculum and pacing in the classroom; (d) societal influences on the school; (e) issues with equity; (t) relationships among stakeholders; and, (g) safe and carmg school/community.
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 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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.037 | 0.020 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".