In-between Spaces: Unconventional Yet Essential Considerations for Defence and Security
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
Dr. Adlakha-Hutcheon discussed dualities between obvious pairs such as defence and security; science and technology; and the physical and virtual worlds and questioned at what point does one become the other? Whether these were truly distinct or continuums with messy middles. Furthermore, it is necessary to understand the middle/liminal spaces between pairs in order to more effectively identify and address security threats. This is apparent when one takes the example of established/emerged and emerging technologies (AI and emergence of generative AI like Chat GPT). Technologies have different impact and implications based on the context of their use, for instance the extent of positive or negative disruption that ensues upon their use. Thus, to address complex problems, it is necessary to look for disruptors in “in-between” spaces. Received: 10-08-2024 Revised: 11-02-2024
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