Reimagining Utopias: Theory and Method in Educational Research in Post-Socialist Contexts. Ed. Iveta Silova, Noah W. Sobe, Alla Korzh and Serhiy Kovalchuk, Rotterdam/Boston/Taipei: Sense Publishers, 2017. Bold Visions in Education Research, Volume 55.
Bibliographic record
Abstract
This peer-reviewed edited collection presents an interesting and eclectic mixture of reflections, accounts, theoretical ideas and analysis of the complexities of doing research in postsocialist settings.The underlying questions and intentions collectively addressed by the authors include: the possibilities of (re)imagining research to articulate new theoretical insights about post-socialist education transformations in the context of globalization; the possibilities of (re)imagining methods to pursue alternative ways of producing knowledge; and ways of navigating various ethical dilemmas in light of academic expectations and fieldwork realities.The attempts to answer these questions are organized around four themes: 1) Researcher positionality, power and privilege; 2) Research, community engagement and activism; 3) Data collection, collaboration and ethics; and 4) Disciplinary paradigms and academic traditions.The geographical scope of the volume includes the countries of the former USSR (Russia, Ukraine, Kazakhstan, Lithuania, Azerbaijan and Tajikistan), its satellite states (Albania, Bulgaria, Poland, Romania, Slovenia and Croatia) and African states (Ethiopia, Zimbabwe, Tanzania and South Africa).The authors of the chapters are 24 researchers, practitioners and activists at different stages of their careers.The majority of the contributors were born in the former USSR or its satellite states and received their research degrees in the global West (the USA, Canada, Australia, the UK).Many of them have now made the global West their academic home; fewer returned back to their counties of origin.Another group of authors are researchers originally from the USA who,
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".