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
Despite the advantages of using instant messaging (IM) for collaborative work, concerns about negative consequences associated with its disruptive nature have been raised. In this paper, the author investigates the mediating role of self-regulation, using a mixed methods approach consisting of questionnaires, focus groups, and interviews. The findings show that these concerns are warranted: IM is disruptive, and multitasking can lead to losses in productivity. Despite these negative consequences, users are active participants in IM and employ a wide range of self-regulation strategies (SRS) to control their overuse. The study found three key SRS: ignoring incoming messages, denying access, and digital or physical removal. The study also found two different approaches to self-regulation. The preventive approach, consisting of creating routines and practices around IM use that would help regulation, and the recuperative approach, consisting of changing behaviors after overuse had occurred. Communication via IM helps in the development of social capital by strengthening social ties among users, which can be useful for information exchange and cooperation. These positive effects provide a balance to the potential negative impact on productivity. Implications for theories of self-regulation of technology and for managerial practice are also discussed.
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 | 0.000 | 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