More lightning in the hand : a case study of the security vulnerabilities of the Osoyoos Port of Entry at the Canada-US Boundary Line
Bibliographic record
Abstract
The purpose of my research was to find answers to the principal research question: “What are the security vulnerabilities of the Osoyoos port of entry, particularly in relation to human trafficking/smuggling and terrorist incursions?” My research sample included eight security experts, specifically, six participants and two collaborators from the local security community in the South Okanagan Valley, British Columbia. The methodology used in my research was a single case study with a two-step approach and an emphasis on qualitative inquiry. Data analysis involved ‘theoretical’ thematic analysis method using three theories. The historical overview provides a historical analysis of border security (and associated security practices and technologies), the Canada-US border, and the Osoyoos port of entry. It also discusses Canadian border security and the intervention of neo-liberalism, the ranking of transnational security threats, Canada’s strategic tradition, and the implications of the changing global threat environment for Canadian national security. Findings reveal that the main security vulnerabilities at the Canada-US border in the South Okanagan region are a robust criminal infrastructure and an under-resourced security community. The findings also reveal that there are many factors that inform and influence Canadian border security policy. Implications for national and public security include the development of high-quality local intelligence, vigilance in analyzing the spatial trends of crime and terror groups, “more predictable and cost-effective screening processes at ports of entry,” and realistic assessments of the resources necessary for a layered security strategy. Recommendations point to the development of high-quality intelligence products, the reinstatement of border resources, and greater specialization of border security personnel.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.034 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".