Bibliographic record
Abstract
Humanity's understanding of complex societal phenomena is still in its infancy, and there is much to discover about the organizing principles governing social life on Earth. How do societal structures such as social hierarchies form, and under what conditions do these structures remain stable versus become unstable and collapse? What is the structure of the jurisprudence that regulates modern human societies and how does it evolve in time? In this thesis, I apply quantitative analysis and modeling approaches from physics and network science to investigate these questions. In Part I, I develop simple models of the formation and stability of social hierarchies and compare their results to interaction data from animal societies and proxy data from human societies. The models are based on pairwise interactions between randomly-selected individuals that result in exchanges of societal "status." Following many interactions, a distribution of status forms, the shape of which ranges from egalitarian (many individuals with near average status) to very unequal (many low status individuals and a few high status individuals), depending on the model parameters. An Arrhenius relationship between a characteristic time controlling the evolution of the status distribution and the model parameters quantifies "long-lived" status distributions which appear to be stable in time, but in fact are not. In Part II, I analyze citation networks of court decisions (judgments) in the areas of family, bankruptcy, and defamation law, using unique datasets covering all levels of the Canadian court hierarchy (trial, appellate, and Supreme Court of Canada). In each network, judgments are "nodes" and judges' citations of past decisions are directed "links" between nodes. Despite the legal differences between the three areas of law, many large-scale network properties are similar. However, one can use refined network tools (clustering methods) to draw out differences in the datasets and interpret them in relation to legal developments (landmark judgments and important legislation) in the specific areas of law. This leads to an in-depth examination of the influence of landmark judgments and statutory changes on the explosion in family litigation that occurred in Canada in the 1990s.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".