Bibliographic record
Abstract
"This book addresses the ethical and methodological issues that researchers face while conducting cross-cultural social research. With globalization and advanced means of communication and transportation, many researchers conduct research in cross-cultural, multicultural, and transnational settings. Through a range of case studies, and drawing on a range of disciplinary expertise, this book addresses the ethics, errors, and ethnocentrism of conducting law and crime related research in settings where power differences, as well as stereotypes, may come into play. Including chapters from scholars across cultures and settings - including Greece, Canada, Vienna, South Africa, India, and the United States - this book provides an invaluable survey of the issues attending cross-cultural social justice research today. Engaging issues confronted by all cross-cultural researchers this book will be invaluable to those working across the social sciences as well as professionals in criminal justice and social work"--
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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.047 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".