Bibliographic record
Abstract
People and Place presents a path-breaking collection of essays demonstrating the fascinating ways in which personalities interact with physical locale in shaping the law. Examining law through the framework of history, this anthology presents a mixture of innovative articles produced by established scholars as well as representatives of the next generation. The collection represents a rich array of interdisciplinary expertise, with authors who are law professors, historians, sociologists and criminologists. Their essays include studies into the lives of judges and lawyers, rape victims, prostitutes, religious sect leaders, and common criminals. The geographic scope touches Canada, the United States and Australia. The essays explore how one individual, or small self-identified groups, were able to make a difference in how law was understood, applied, and interpreted. They also probe the degree to which locale and location influenced legal culture history. The essays offer snapshots of human history, capturing the centrality of law as individuals located themselves in relation to others and to the places and times in which they lived. Accessible to academics, students, and general readers interested in the formation of law within a social context, this collection offers a compelling perspective of this subtle relationship. The close examination of people and place will allow readers to unpack law’s various meanings across communities and time, and to move closer to a more profound awareness of the complexity of human society.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".