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
Jeremy Wood, places, code and GPS are the protagonists in his personal cartographies. He plots the journeys, bicycles, boats, planes and his two feet provide him mobility, and geography is the precept, all of which are mediated by the communication infrastructure. Land, water, air and the engineered environment of places determine the routes, are the medium within which his body moves and are the settings where he performs his traces. Time, location and established measurement standards, along with geodetic models, radio signals, software, the language of culture and place, encode the narrative voice. GPS is his cartographic rendering tool: it is what points, traces, locates and recounts. Cartography is his narrative mode: it is that which conveys his personal narrative. This article is about a series of conversations mediated by telephone, Skype, email and online chat functions. We discussed Wood's personal cartographies, how these journeys tell him where he is, has been and potentially where he is going. These are personal cartographies, the result of individual journeys that he is assembling. His GPS tracings make us privy to his personal data, which tell us something about him while questions about science, cartography and technology also become conspicuous. The focus is on the Data Cloud outdoor installation, the Meridian performance and Lawn Mowing experiments. Wood's work is playful, yet it also critically foregrounds the fallacy of technological accuracy and the imprecision of stories. Where he is and where things are positioned are inaccurate from a GPS point of view, since GPS is engineered imprecision. This lack of specificity changes the location of things in space ever so slightly, but just enough to confound physical reality as we see in the Data Clouds outdoor installation. However, are stories ever definitive accounts of an experience? And what of the models by which we understand the world? What if we are between spatial models and some spaces are nowhere to be seen? Does that mean the place does not exist? What does it mean to be there but lost in space? What does it mean for a place to exist in the first place? His Meridian performance of the Herman Melville quote 'It is not down in any map; true places never are' elucidates this special conundrum in both literal and metaphorical terms. He traces the words along two meridians drawn according to two different but scientifically approved mathematical models of the earth, GMT and GRS80. Ironically, true places are written in Greenwich Park, the very same location where time and space were established as a standard in 1884.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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