Legitimizing Security in the Ivory Tower: Canadian University Corporate Security Services’ Public Quest for Legitimacy
Bibliographic record
Abstract
This article examines how university corporate security (UCS) services engage in legitimation work in their attempts to make their university communities (i.e., faculty, staff, students) and political masters (i.e., university administrators, boards of governors, senators) believe that they are honest, trustworthy, and caring and have authority that should be deferred to. This is accomplished through the analysis of interview and observational data collected as part of a research project exploring UCS services at five Canadian universities and an examination of how UCS services at 14 Canadian universities communicate using the social media service Twitter. These UCS services were found to primarily use Twitter for the purposes of soliciting or requesting information and for networking. In communicating through Twitter, UCS services engage in public legitimation work in which they make claims about and attempt to demonstrate their expertise, authority, and accountability. This article argues that both UCS services' particular legitimacy problem (i.e., their possession of both private and public attributes) and the interactive nature of public legitimation work create tensions that may serve to disrupt UCS services' ability to attain legitimacy. Cet article examine la manière dont les services de sécurité d'entreprise à l'université (SEU) s'engagent à légitimer leurs tentatives de persuader leurs communautés universitaires (c'est-à-dire le corps professoral, le personnel et les étudiants) ainsi que la haute administration (c'est-à-dire les administrateurs de l'université, le conseil des gouverneurs et les sénateurs) qu'ils sont honnêtes, attentifs, dignes de confiance, et qu'ils possèdent un niveau d'autorité auquel quiconque devrait se référer. Ceci sera accompli en analysant un corpus d'entrevues et d'observations dans le cadre d'un projet de recherche examinant les services de type SEU dans cinq universités canadiennes, ainsi qu'une étude sur la manière dont les services de SEU dans quatorze universités canadiennes gèrent leurs communications sur le réseau de médias sociaux Twitter. Il a été établi que ces services de SEU utilisent principalement Twitter pour la sollicitation ou la demande d'informations, et pour le réseautage. En communiquant par Twitter, les services de SEU s'engagent dans un processus de légitimation par lequel ils revendiquent et tentent de démontrer leur expertise, autorité, transparence et responsabilité. Cet article propose l'argument suivant: la question de la légitimité particulière des services de SEU (c'est-à-dire leur possession d'attributs à la fois privés et publics) combinée avec la nature interactive du processus de légitimation publique crée des tensions qui peuvent en fin de compte perturber la capacité des services de SEU à atteindre réellement cette légitimité.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".