Volunteered Geographic Information: the nature and motivation of produsers
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
Advances in positioning, Web mapping, cellular communications and wiki technologies have surpassed the original visions of GSDI programs around the world. By tapping the distributed knowledge, personal time and energy of volunteer contributors, GI voluntarism is beginning to relocate and redistribute selected GI productive activities from mapping agencies to networks of non-state volunteer actors. Participants in the production process are both users and producers, or ‘produsers ’ to use a recent neologism. Indeed, GI voluntarism ultimately has the potential to redistribute the rights to define and judge the value of the produced geographic information and of the new production system in general. The concept and its implementation present a rich collection of both opportunities and risks now being considered by leaders of public and private mapping organizations world-wide. In this paper, the authors describe and classify both the types of people who volunteer geospatial information and the nature of their contributions. Combining empirical research dealing with the
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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