Bibliographic record
Abstract
Augmenting jurisdiction is a hypothetical scenario I have created, to explore what impact Mixed Reality (MR) could have on the Environmental Court of Aotearoa (EVC A). This Thesis has two equal sides of exploration; Physical and Virtual. The ‘Physical’ in this instance is the hierarchy and organisation of the Environmental Courts of Aotearoa and the ‘Virtual’ are the components and concepts of Mixed Reality. Stage One of the research is exploring the Physical - hierarchy, technological and organisational requirements of EVC A, as set of out by the Ministry of Justice and Courts NZ . Within this stage of research I explore the statutory bodies, resource management act and the compositional structure of the judicial system. I also explore the variable of the Virtual - the concept of MR, as set out by Prof. Paul Milgram, Ph.D., P.Eng. from the ETC lab at the University of Toronto. It explores technologies that are currently under research and development and are not necessarily available to the general public. However these products contain the possibilities for what I am proposing in this paper. Exploring the capabilities of MR delves into products such as “Google Glass” or other Head Mounted Displays (HMD), Heads Up Display (HUD), both material and immaterial video display and graphic simulated environments. Stage Two is extrapolation and interpretation of the Physical and the Virtual constructs. The data from Stage One regulated how I approached the design. The model created in Stage Two is a direct result of the contraints colated in Stage One and the physical parameters of the old Ministry of Defense building, 15 -21 Stout St, Wellington. Stage Two was completed with computer aided design so" ware from companies such as Autodesk, Adobe and others. Stage Three - Exogesis - reflection and evaluation. This stage was to culminate my ideas and research. I would like to thank you for reading this thesis and hope you have a nice day :)>
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 0.003 |
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".