Bibliographic record
Abstract
In this video, we present a system called Artifact Buddy, which is grounded on the premise that an unaltered Instant Messenger system can simultaneously provide both artifact awareness and interpersonal awareness. In Artifact Buddy, artifacts and people are treated the same way. An artifact – in this case a Microsoft Word document - becomes a first-class IM buddy and behaves like other buddies within a defined group. The artifact-as-buddy knows which people are interested in it and notifies these individuals about its state. Group members can interact with the artifact (and the rest of the group) through the IM system’s standard chat features. Critically, this is all done with a client-side helper application that exploits an existing and unaltered IM system. The IM system does all the heavy lifting: it does the underlying distributed systems work, communication, account control, and so on. For a group that already uses this common IM program, all that is required is that one group member install a helper application to run in the background. Additionally, because our approach takes advantage of the interaction mechanisms already well established by IM, group members can readily join and participate in collaborations without requiring that they learn how to use a completely new application. We built Artifact Buddy as a working technical illustration of how artifact awareness can be feasibly integrated into an existing instant messenger. The Artifact Buddy system implements a user interface and a wrapper around Microsoft’s Live™ Messenger service. We chose Live Messenger because it has functions typical of most IM services, as well as a public API; we use the open-source DotMSN library to access Live Messenger functions. Through this API, Artifact Buddy programmatically invokes activities such as inviting buddies, setting and receiving state information, sending and receiving chat messages, initiating and responding to file exchanges, and so on. Importantly, Artifact Buddy is not a distributed system. Rather, it is a local application that relies completely on the underlying capabilities of the Live Messenger IM infrastructure to connect and to distribute chat data, status messages and files to others. This video illustrates the key features of Artifact buddy. A companion paper [1] details its background, further features, and intellectual contributions. References [1] Greenberg, S., Voida, S., Stehr, N. and Tee, K. (2010) Artifacts as Instant Messaging Buddies. 11th Persistent Conversation Minitrack, Digital Media and Content, Hawaii International Conference on System Sciences – HICSS’10, (Kauai, Hawaii, January 5-8),IEEE.
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How this classification was reachedexpand
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) | 0.003 | 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; both teacher heads agree on what is shown here.
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".