Bibliographic record
Abstract
In July 2002 Bell Canada’s Wired and Wireless Center 1 (WCC) conducted a field trial implementation of Panasonic’s latest wearable computer, the CF-07. This pilot was part of Bell’s larger wearable computing initiative that had as a motto the creation of a ‘mobile, wireless and wearable ’ workforce. From the WWC’s perspective this pilot was a fairly straightforward procedure. It involved a mere ‘technological replacement’—from the old laptop to a new wearable. For Bell managers, this was a minor change, a change in form not function, since the functionality of the previous laptop computing device had remained the same. Technicians were simply being given a more appropriate tool to perform their jobs. However, as this paper will demonstrate, the process was far more complicated. It involved the transformation of a stable network of identities, that of Bell’s field technicians into a new hybrid entity: augmented field technicians. In the course of this project, actors that the WWC had not foreseen turned out to play a major role in the development of the pilot project; the technological artefact did not manage to sustain its identity as a wearable computer; and technicians interpreted the shift to wearable computers as an alteration of the character of the job itself, and thus, of their role within it. This paper highlights the complexity of the attempts to create this ‘new ’ hybrid entity—human and machine, body and computer—and argues that part of this complexity derives from the fact that it presupposes a change in the entity’s reality and identity. A technician equipped with a wearable computer, that shares his cognitive and personal space, is qualitatively different from that of the ‘field technician’. 1 Throughout this paper pseudonyms will be used to identify departments and individuals within the companies herein mentioned. Ana Viseu – Creating Augmented Technicians 1/27
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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 | 0.008 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.569 | 0.451 |
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; the direct Gemma label and the distilled Codex classifier 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".