Anomalies of territory: examining the relationship between territory, sovereignty, and statehood
Bibliographic record
Abstract
This thesis examines the nature of the legal relationship between territory, sovereignty and statehood in the face of assertions that state sovereignty is being undermined by globalization and climate change. In response to these challenges, this thesis asserts that, in the context of state control and sovereignty, the role of territory is not static but rather elastic, and that this elasticity has allowed for the growth and development of the state as a theoretical and practical legal construct throughout a spectrum of new challenges. The thesis establishes what is termed the model of legal elasticity and the imperium and dominium relationship in order to evaluate the relationship between territory, sovereignty and statehood. âLegal elasticityâ refers to flexibility of control over territory and of state policies relating to territory in the face of growing, developing, changing and/or challenging legal and political situations. This flexibility accommodates different legal systems, governance structures and populations without weakening or undoing state control and the state itself. To support the application of legal elasticity, the thesis uses a modified version of the Roman law relationship between imperium and dominium to explain how a state maintains overall territorial control and sovereignty while at the same time allowing for legal elasticity within the confines of its borders. The model of legal elasticity and the imperium and dominium relationship is next applied to identified key periods of growth, development, change and/or challenge to legal constructs of territory and state territorial control in the domestic and international law realm. The thesis then applies the model to current day forms of anomalies of territory, sub-categorized as anomalies of economy, anomalies of politics and anomalies of military. The application demonstrates the strengths of the model as well as the many situations in which it has been used, albeit without being referred to as such, throughout different legal systems. Based on this, it is the assertion of this thesis that current challenges such as globalization and climate change might require a shift in the imperium and dominium balance within the state but that legal elasticity allows for this to occur without undermining the relationship between territorial control, sovereignty and statehood.
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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".