Switching Cars with the Militsiya and Other Ways the Finnish–Russian Borderland is ‘Lived’ by People in Their Everyday Lives
Bibliographic record
Abstract
Borderlands differ from more central areas of states as they are affected by different border effects, such as cross-border flows and the intermingling of societies and cultures. Yet, the ways people experience and practice borderlands by attaching meanings to the material and social space have received relatively little attention. The present study focuses on the Finnish–Russian borderland as ‘lived’ by people in their everyday lives. It is based on ethnographic fieldwork conducted in the Finnish border cities of Imatra and Lappeenranta and the Russian border cities of Svetogorsk and Vyborg in 2017 and 2018. The main finding is that the participants’ cross-border practices are intertwined with personal and socially shared meanings that they associate with the borderland and places within it. These meanings also play an important role in the ways the participants form relationships with the borderland. The paper argues that research on borderlands needs to pay more attention to the ever-evolving relationship between people and space for deepening the understanding of the specificity of borderlands as living environments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".