Ecological Interface Design for Network Management
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
This paper describes an experimental investigation of Ecological Interface Design (EID) in computer network management. The constant potential for the addition and removal of devices, as well as change of configurations, makes this work domain more fluid than those previously studied under EID. Two interfaces were created for the University of Toronto campus network consisting of 220 nodes: a P interface based on existing design practices which presented primarily physical information and a P+F interface based on EID which presented both physical and functional information identified by an abstraction hierarchy analysis. Participants were required to use one of the two interfaces to detect and diagnose faults or disturbances in the network in real-time. Network size and fault load were both manipulated as within-participants variables. The P+F interface led to faster detection times, improved rates of detection under higher fault loads, and more accurate diagnoses under higher fault loads. These results suggest that the EID framework may lead to more robust monitoring in computer network management compared to existing interfaces.
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 | 0.001 | 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 | 0.001 | 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) | 0.000 | 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