Bibliographic record
Abstract
Corporate security is a form of regulation that involves centralized management of access control, physical security, personnel security, and information security inside an organization. For all the research on public policing, national security, and private contract security in sociology, criminology, and related disciplines, little scholarly attention has been paid to corporate security. Increasingly, corporate security is playing an important role in municipal and other government organizations as well as its traditional private, corporate domain. This book is the first social scientific contribution on corporate security to draw together the sociologies of security and policing, legal and social theory, and debates about municipal government. In this book, Walby and Lippert conceptualize various types of corporate security, including its public and private forms, and analyze a range of practices, such as asset protection and physical security provision. The authors explore a number of heretofore neglected themes, including use of legal knowledge, professionalization, legitimation work, and corporate security links with other security agencies and public police. The book provides empirical analyses of developments in several countries, but especially Canada and the US, where corporate security - including its entry into municipal government - is particularly advanced. Because corporate security cuts across security, policing, law, and government, as well as issues of professionalization, public space and democracy, the readership for Municipal Corporate Security in International Context spans disciplinary and national boundaries. It is essential reading for academics and students engaged in studying security, urban governance, politics and legal regulation. It will be of great interest to corporate security professionals and government policymakers too.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".