Doing Educational Research in Rural Settings: Methodological issues, international perspectives and practical solutions
Bibliographic record
Abstract
Introduction: This book is aimed broadly at educational researchers, and in particular graduate students, whose research interests are located outside metropolitan areas in places that are generically considered to be rural.This book is both timely and important as no other text currently takes up the key question of how to conduct educational research within and for rural communities or seeks from an inquiring stance to explore the impact of educational research in rural contexts in terms of the lasting 'good' of research to those being researched about.We believe that current interest in space and place as well as in urban education creates a novel and parallel opportunity to explore educational scholarship through a rural lens.The authorship of our text is international bringing together researchers experienced in conducting educational inquiry in rural places from across European, Australian, American, and Canadian contexts discussing national and regional challenges and ways of working into conversation.It also draws from the research experiences of the most senior 'elders' in the field of rural educational research as well as those in their early career as they share their research methodological issues such as unpacking their own subjectivities; considering ethics of confidentiality/pseudonymity in places where often everyone is well known and identifiable; thinking about reciprocity and converging interests; and notions of identity and representation.This book is uniquely written with an eye to practicality and applicability for a higher degree and doctoral research market and offers a compelling international comparative perspective addressing a key criticism that rural education research tends to be too locally-focused, nostalgic or insufficiently attuned to the effects of globalization. Chpater 7Researching within and for a rural community: a research journey.
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 | 0.137 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.011 | 0.062 |
| Scholarly communication | 0.034 | 0.029 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.008 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".