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
The usability of access control mechanisms in modern distributed systems has been widely criticized but little studied. In this paper, we carefully examine one such widely deployed access control mechanism, the one embedded in the WebDAV standard, from the point-of-view of an end-user trying to decide how to grant or deny access to some resource to a third party. This analysis points to problems with the conceptual usability of the system. Significant effort is required on the part of the user to determine how to implement the desired access rules; the user, however, has low interest and expertise in this task, given that such access management actions are almost always secondary to the collaborative task at hand. The analysis does however indicate a possible solution: to recast the access control puzzle as a decision support problem in which user intentions (i.e. the descriptions of desired system outputs) are interpreted by an access mediator that either automatically or semi-automatically decides how to achieve the designated goals and provides enough feedback to the user. We call such systems intentional access management (IAM) systems and describe them in both specific and general terms. To demonstrate the feasibility and usability of the proposed IAM models, we develop an intentional access management prototype for WebDAV. The results of a user study conducted on the system show its superior usability compared to traditional access management tools like the access control list editor.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it