Bibliographic record
Abstract
Purpose This study aims to present the findings of the first phase of a project entitled Putting the “Fun” Back in “Functional”, which has been investigating the socio-technical issues surrounding users’ interaction with electronic recordkeeping systems. The ultimate goal of the project is to improve that interaction by positively influencing the way in which individuals perceive their work practices and the tools they use to accomplish them. In its first phase, the project considered the implementation of such systems for the purpose of gaining a better understanding of the factors and processes that contribute to its success. Design/methodology/approach Semi-structured interviews were conducted with 17 public employees from a large provincial government and a large city government in Canada about two information systems (ISs) – a meeting management system and an Electronic Documents and Records Management System. Findings Several salient themes emerged from the research data, including the value accorded to information and records, the implementation of electronic recordkeeping systems as a complex process, the appropriation of electronic recordkeeping systems, understanding users, ease of use and information/records specialists as part of the solution. Analysis of these themes shows that many of them can be explained through theories developed in the IS field. Research limitations/implications The results show that many themes are common across the records management and IS fields. Further, the results indicate the applicability of theories in the IS field to explain and predict the implementation of electronic recordkeeping systems. Originality/value This study is one of few that explicitly draw on IS theories to understand the implementation of electronic recordkeeping systems. The results of this study open up many opportunities for future research on electronic recordkeeping systems.
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 | 0.019 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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 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".