Cardinal: Novel software for studying file management behavior
Bibliographic record
Abstract
ABSTRACT In this paper we describe the design and trial use of Cardinal, novel software that overcomes the limitations of existing research tools used in personal information management (PIM) studies focusing on file management (FM) behavior. Cardinal facilitates large‐scale collection of FM behavior data along an extensive list of file system properties and additional relevant dimensions (e.g., demographic, software and hardware, etc). It enables anonymous, remote, and asynchronous participation across the 3 major operating systems, uses a simple interface, and provides value to participants by presenting a summary of their file and folder collections. In a 15‐day trial implementation, Cardinal examined over 2.3 million files across 46 unsupervised participants. To test its adaptability we extended it to also collect psychological questionnaire responses and technological data from each participant. Participation sessions took an average of just over 10 minutes to complete, and participants reported positive impressions of their interactions. Following the pilot, we revised Cardinal to further decrease participation time and improve the user interface. Our tests suggest that Cardinal is a viable tool for FM research, and so we have made its source freely available to the PIM community.
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How this classification was reachedexpand
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".