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
Borders have recently attracted a lot of academic scrutiny. Two very distinct types of literature have attempted to capture the current evolution of borders. The first one, leaning more toward the field of security studies, puts the emphasis on the rampant securitization, the coercive dimension of borders, and their divisive consequences. The second, looks at the rich environment surrounding borders, where boundaries are seen as the meeting point of a variety of cultures and communities. Those social spaces, known as borderlands, are the cradle of hybrid identities and transnational networks that contest the State’s claim to ultimate sovereignty over its territory. Against this backdrop, the ambition of this special issue lies in its aim to fill theoretically and empirically this gap by looking at securitized borderlands. This introductory article delineates the contours of and puts together the main findings of both security studies on borders and borderlands studies. It announces the objectives of the subsequent articles, which together look into the interaction between the securitized borders and the social spaces they both obstruct and dynamize. In spite of and within this peculiarly adverse environment of “securitized borderlands,” cross border societies remain in existence, resist, comply, and adjust.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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