Bibliographic record
Abstract
Borders remain vitally important features of our political world. Throughout the Global North, the common response to the broad challenges and the multiple overlapping crises has been to regress to state-centric thinking and nationalist agendas and revert to ad-hoc border closures. We have witnessed a consistent drive for ever stricter border and migration policies, which are not limited to the mere border management, but become an inherent part of a wide range of polices and societal practices. The premise assumed herein is that borders do not only divide physical space, but are also used increasingly to sort people according to the degree of their belonging. The question under scrutiny here is that how to balance the calls for the freedom of movement against the right to freedom of association? I seek to unravel this conundrum by addressing the arguments used to support these, which might appear as inherently, opposite stands. In advocating for unbounded inclusiveness, I seek to challenge the widely accepted notion that people are from a certain territorially demarcated place, and their rights, duties – and opportunities in life, ought to remain based on their arbitrary fact.
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 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 | 0.034 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.122 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.012 | 0.020 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".