On being education nomads:Mongolian herders’ children straddling ways of knowing and relating
Bibliographic record
Abstract
On Being Education Nomads explores how the convergence of pastoralism, schooling and digital ICT development shapes the education and future aspirations of Mongolian herder’s children. Drawing on visual participatory data, semi-structured interviews and qualitative surveys that are grounded in multi-sited ethnographic research, it demonstrates that Mongolian herder’s children become education nomads by straddling the herder and schooled urbanite communities of practice. Deploying education nomads as a generational identity marked by Mongolian rural youth’s concurrent participation in herding, schooling and digital practices, this research maps out how herder’s children orient towards urban professional aspirations while building their capacity to navigate Mongolia’s rural-urban continuum for multiple futures. Using a generationed and socio-ecological approach to development, this research examines not only how education shapes learners and the places that they inhabit but also how learners shape education and their learning socio-ecologies. This manuscript adds young people’s experiences to the literature on Mongolia’s development and brings a development perspective to the sparse body of literature on Mongolian childhood and youth. Foregrounding the perspectives and lived experiences of rural young lives from a non-Western and non-sedentary society, On Being Education Nomads contributes critical insights on the crosscutting themes of mobility, education, aspiration and ICT4D to the field of children and youth studies.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".