Bibliographic record
Abstract
The Mobile Media Lab (MML) is a Canadian interdisciplinary research team exploring wireless communications, mobile technologies and locative media practices. By developing interactive mobile experiences, we observe and reflect on the dynamics inherent in wireless immersive environments connected to a growing tendency towards ubiquitous computing or pervasive media. Our projects, whilst rooted in digital ephemera, treat physical territory as an active and volatile interface creating networked situations to connect the physical to the virtual. Our intention is to use media to quietly augment everyday life and to initiate novel ways of telling stories of the past by harnessing digitally rendered images, text and sounds. In our chapter, we will focus on two projects, Urban Archaeology: Sampling the Park and The Haunting, which were part of our work done under the rubric of the Mobile Digital Commons Network (MDCN, 2004-2007). We will use the phrase voices from beyond as a trope in our reflections upon the deployment of mobile media technologies and use of locative media practice to intentionally blur past and present moments. As we argue, archival fragments and ghostly images can be presented via handheld devices to use the power, potential and public intimacy of media dependent upon the presence of electromagnetic spectrum. In addition to key texts on locative media, we draw on Benjamin’s understanding of history as a sensibility whereby the past and present co-mingle in the minds and embodied memories of human subjects, Darin Barney’s notion of the “vanishing table” as an alternative means for engagement in technologically mediated zones of interaction, and writing on communications theory that deals with the spectral qualities of new media (Sconce; Durham Peters; Ronell).
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 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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".