Bibliographic record
Abstract
Classified as populations less than 1000, 16.1% of Alberta’s population lives rurally (Alberta Government, 2016, p. 3). Rural education research addresses an underserved minority in educational structures, policy and practices. However, much of the research is approached in a way indicating the rural is somehow deficient. Well cited researchers in the field of rural education research, Howley and Howley (2014) state, “the most prevalent impulse in rural education research is to address the problem of rural schools, namely that they are deficient and need to be improved. Variations on this theme implicate the deficiencies of rural children, rural families, rural teachers, rural school facilities, rural culture, and so on” (p. 10). As someone who grew up rural and remains deeply tied to it, I have witnessed variations of these themes in theory and in practice. In order to see what possibilities lay ahead for rural education research, we ought to consider where we have been. Howley and Howley’s (2014) assessment is a call to do rural research differently. Being focussed on the problem can obscure or preclude what is important or valuable within rural communities regarding educational research. In part due to Howley & Howley’s assessment and in part because of a curiosity that drives my own present and future forms of research, I present a literature review of The Journal of Research in Rural Education. I examine the abstracts covering the years between and including 2012-2020, where I determine whether their pronouncement rings true over the past decade. Since Howley and Howley published their assessment, the continuing research in JRRE has remained fairly consistent with the prevalent impulse to problematize the rural in an educational capacity. In my findings I do the following, 1) assess the proportion of research problematizing some aspect of the rural in rural education research, 2) contextualize reasons for and against the impulse to address “the problem of rural schools,” and 3) optimistically look to studies that are not framed by assumptions of deficiency in rural communities. I look to the latter in order to envision new possibilities for doing rural educational research for rural communities rather than on rural communities. References Alberta Government. (2016). 2016 Census of Canada – Population and dwelling release. https://open.alberta.ca/dataset/7d02c106-a55a-4f88-8253-4b4c81168e9f/resource/e435dd59-2dbd-4bf2-b5b6-3173d9bd6c39/download/2016-census-population-and-dwelling-counts.pdf Howley, C. & Howley, A. (2014). Making sense of rural education research: Art, transgression, and other acts of terroir. In S. White & M. Corbett (Eds.), Doing educational research in rural settings: Methodological issues, international perspectives and practical solutions (pp. 7–25). Routledge.
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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 | 0.438 | 0.624 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.023 | 0.032 |
| Science and technology studies | 0.016 | 0.095 |
| Scholarly communication | 0.043 | 0.086 |
| Open science | 0.009 | 0.018 |
| Research integrity | 0.028 | 0.045 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".