“Who Is the Animal in the Zoo?” Fencing In and Fencing Out at the Hungarian-Serbian Border. A Qualitative Case Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In 2015, Hungary commenced the building of a fence at its border with Serbia. The current article investigates the Hungarian-Serbian border fence in terms of its meaning in the two countries. Building on recent re-bordering research, it analyzes the context within which the fencing took place, stressing both the domestic and the international dimension. Based on qualitative interviews and a document analysis for Hungary and Serbia, it argues that the fence did not create a conflict between the two neighbors – instead, the international entanglement of the border led to a complex bordering process that extended bilateral relations. In Hungary, the border fortification was used for internal political motives and at the same time aimed to exclude non-European migrants. Due to political circumstances and the filter function of the fence, the Serbian government likewise managed to exploit the border fortification to its advantage. The article introduces the concept of “fencing in and fencing out” in order to analyze the control function that the fence performs on both sides of the border.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it