An Exploratory Study on Behavioral and Emotional Coping with IT-Enabled Government Surveillance
Bibliographic record
Abstract
Despite the growing literature on the notion of Data Privacy Concern, we lack an agreed upon conceptualization and operationalization of this overarching construct. The present paper argues that the concept of privacy is highly context-dependent and that its proper conceptualization requires the specification of the nature of the data involved, as well as the identity of the perceived data violator. Based on this idea, as well as Folkman et al.' s [11] eight ways of coping as a conceptual framework, we describe an exploratory study we undertook to examine individuals' behavioral and emotional coping approaches to online intellectual privacy and governments as potential violators of online intellectual privacy. A qualitative analysis of 206 online textual comments made by surveillance news readers led to the identification of three behavioral coping mechanisms, i.e., confrontive_B coping, enlightening and self-control, as well as five emotional coping mechanisms, i.e., delusional thinking, self-control, confrontive_E coping, escape-avoidance and positive appraisal.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".