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
The goal of this second report is to review how social media are changing the way we collectively map the world. To reach this goal I review different collective mapping practices that characterize the social media era. First I examine the situation of community mapping in the context of new cartographic processes and technologies, with a focus on indigenous cartographies. I then review the use of volunteers in the production and representation of geospatial knowledge, with an emphasis on crisis mapping. Finally, I discuss how map-making in the social media era reflects major trends in terms of power relationships that occur between the state, its citizens and the private sector. These trends reveal the replacement of the state as the main reference for the collection and dissemination of cartographic data, by a combination of private interest and individually volunteered contributions. Just as the specific interests of the nation state have largely helped to shape the reality produced by paper maps throughout the centuries, this new convergence of interests is now helping to shape the reality produced by digital maps through geosocial media.
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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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