A Review of Measures of Disclosure Outcomes in the IS Privacy Literature
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
For twenty years, Information Systems (IS) researchers investigated privacy attitudes and disclosure outcomes, yet a full understanding of the privacy disclosure relationship has not been reached. In the current study, we argue that the lack of consensus regarding the privacy-disclosure relationship may stem, at least in part, from methodological shortcomings. We contend that variations in disclosure measurement practices may be responsible for ambiguous findings in the accumulated IS privacy research. We provide a preliminary review of the IS privacy literature from which we aim to build an initial foundation for recommendations regarding measures of disclosure outcomes. We identify four widely used measures of disclosure outcomes (i.e. intentional, breadth of, retrospective self-reports of, and actual disclosure) and discuss their methodological concerns. We conclude with a brief discussion on the methodology for the full review and recommendation for future research.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it