Bibliographic record
Abstract
Users of social networking websites tend to disclose much personal information online yet seem to retain some form of an expectation of privacy. Is this expectation of privacy always unreasonable? How do users of online social networks define their expectations of privacy online? These questions were the impetus behind an empirical study, the findings of which are presented in this Article. The project, simultaneously conducted in Canada, at Ryerson University, and in the United States, at the University of Miami, consisted of a survey regarding personal information protection and expectations of privacy on online social networks (OSNs). Approximately 2,500 young adults between the ages of 18 and 24 were surveyed about the personal information they post online, the measures they take to protect such information, and their concerns, if any, regarding their personal information. Respondents also reacted to several hypothetical scenarios in which their privacy was breached on an OSN by measures both within and beyond their control. The theoretical assumption underlying this research project is that two prevalent and competing notions of privacy online exist: one rooted in control and the other in dignity. Of the two, the idea of privacy as control over one's personal information has, to date, been predominant. Legislation, regulation, corporate policy, and technology are often analyzed and evaluated in terms of the measure of control offered to individuals over their personal information. Leading OSNs, such as Facebook and MySpace, propagate a notion of privacy as user control. However, online social networking poses a fundamental challenge to the theory of privacy as control. A high degree of control cannot preclude the possibility that online socializers would post unflattering, defamatory, or personal information about each other, and that this information would in turn be available to a large, if not unrestricted, online audience. Many online socializers post personal information seemingly without much concern over the loss of control, yet it seems that online socializers react with indignation when their personal information is accessed, used, or disclosed by individuals perceived to be outside their social network. The findings presented here indicate indeed that online socializers have developed a new and arguably legitimate notion of privacy online, that if accepted by OSNs, will offer online socializers both control and protection of their dignity and reputation. We call this notion network privacy. According to network privacy, information is considered by online socializers to be private as long as it is not disclosed outside of the network to which they initially disclosed it, if it originates with them, or as long as it does not affect their established online personae, if it originates with others. OSNs, as businesses profiting from socializing online, are best positioned to offer online socializers, often the young and vulnerable, effective protection in accordance with their notion of network privacy above and beyond regular measures of personal information control, and they should be required to do so.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.033 |
| Scholarly communication | 0.016 | 0.031 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".