Secure decommissioning of confidential electronically stored information (CESI): A framework for managing CESI in the disposal phase as needed
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
Retention and disposal of confidential information by an organization requires diligence. Unfortunately, the current disposal methods of Confidential Electronically Stored Information (CESI) have resulted in many security breaches and violations of existing regulations. As financial & litigation risk, loss of consumer confidence and detrimental business reputation are realities of security breaches, the objective of this research is to propose a framework for processing of CESI securely, during the disposal phase, utilizing the “sandbox” methodology to process and sanitize CESI. This is achieved by introducing categorization of information groups and using a classification scheme to depict the level of confidentiality quantified by a “value portfolio”. The thresholds in the value portfolio enables organizations to establish clear and practical security policies in processing and disposing of ESI during the Information Life Cycle (ILC).
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 | 0.000 | 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