Perspectives of a Rural Music Educator: A Narrative Journey Through 'Sense of Place'
Bibliographic record
Abstract
There is a scarcity of research in contemporary rural studies in Canada, particularly pertaining to education. Discrepancies exist in definitions of rural and rurality. What is the meaning of rural, and how do educators define their teaching praxes? This study explores how one music teacher negotiates her role identity in a rural setting through the conceptual framework of sense of place, and how ‘place’ influences her education praxis. Grounded in the narrative methodological perspectives of Connelly and Clandinin (2006), this study investigates the lived experiences of one educator from a place-based lens. Findings indicate that a place-based curriculum may highlight positive aspects of rural areas, address shortcomings, and encourage rural youth to return to their rural roots.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.033 | 0.029 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.008 |
| 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".