Bibliographic record
Abstract
The establishment and operation of an electronic records management system has become an essential requirement for the systematic and safe management and preservation of the increasing electronic records of institutions. However, in addition to cost, various external conditions have made it difficult for universities to implement electronic records management systems. Therefore, some institutions abroad are using shared drives as an alternative to their electronic records management system. The shared drive refers to a technique of using an external hard disk together among a plurality of host networks through a LAN (local-area-network), which is a local area network. It is a role to share files among users on LAN so that other users can use files together. This study aims to investigate and analyze the guideline of using shared drive in foreign countries as an alternative for electronic record management of university. Examples of records management by overseas universities using such shared drives include York University in Canada, Curtin University in Australia, and University of Wisconsin in the United States. As a result of the analysis of the cases, it was confirmed that the shared drive utilization guideline items shared by two or more universities of three universities have responsibility, disposal, security, file name change, shared drive structure, and file plan. In the future research, we will analyze the cases of public institutions in addition to the university, and design guideline for the use of the shared drive according to the situation of the Korean university which is not able to introduce the electronic record management system.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".