Bibliographic record
Abstract
The relation between the concepts of sovereignty and citizenship are being rearticulated through what is popularly referred to as ‘Fortress North America’. The ‘War on Terror’ has amplified previously emerging shifts in governance, control and surveillance. One significant consequence is the development of increasing border harmonization schemes between the United States of America and Canada. This development has led to newly emerging technologies of citizenship in both Canada and the USA. This paper pays particular attention to the shifts that are taking place with regards to the revocation of citizenship, the creation of new categories of citizenship through programs such as ‘Nexus’ and the proposed introduction of bio‐metric ID cards in Canada and the introduction of the discourse of the ‘new normal’. Through new border harmonization programs established in the ‘Smart Border Declaration’ citizens and non‐citizens in both Canada and America will be organized, controlled and subjected to new forms of state surveillance. The discourse of the ‘new normal’ is meant to signal a shift in our expectations of daily life. Whether we are experiencing the ‘new normal’ due to disease, fear, risk, loss of faith or security, we are being called into place as subjects of this discourse. The ‘new normal’ is used in reference to the need for greater control, the expectation of greater security and surveillance of cells, microbes, bodies and society. This paper will explore the logic that is embedded within the discourse of the ‘new normal’.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.034 | 0.077 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".