EXPLORING URBANITY IN ALMATY & NUR-SULTAN: AN OVERVIEW OF A MAJOR RESEARCH PROJECT
Bibliographic record
Abstract
This paper showcases the logic, methodology, and findings features in Dmitrenko’s Major Research Project submitted to the University of Toronto for partial fulfilment of the requirements for the Master of Arts degree. Dmitrenko’s research focused on exploring city development as an agent of political development in Kazakhstan. Exploring Almaty and Astana as her two case studies, Dmitrenko argues that the concurrent growth of both cities tells a story of Kazakhstan’s complicated relationship between the government and its citizens. In navigating these bottom-up or top-down relationships between the government and its citizens, Kazakhstan’s urban space seems to be organizing itself according to the principle of digitalization – the idea that digitalization can improve institutional trust and the quality of life. In doing so, Kazakhstan may be carving out a path for a new kind of political development.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".