Instant Messaging for Collaboration: A Case Study of a High-Tech Firm
Bibliographic record
Abstract
This article examines uses of instant messaging (IM) in a high-tech firm to illustrate how knowledge workers use this new work tool to collaborate with co-workers. The objectives are 1) to identify the collaborative practices of individuals in mediated work environments by looking at uses of IM; 2) to discern what social processes are reflected in employees' use of IM; and 3) to investigate how three factors proposed by Erickson and Kellogg (2000) to support social processes—visibility, awareness and accountability—are used in an IM system. Questionnaire and interview data show that while IM leads to higher connectivity and new forms of collaboration, it also creates distance: employees use the mediated environment as a shield, distancing themselves from superiors. We use Erickson & Kellogg's ‘social translucence of technology’ framework to discuss the social consequences of working in a computer-mediated work environment.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".