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
Conservationists, governments, and corporations see promise in digital technologies to provide holistic, rapid, and objective information to inform policy, shape investments, and monitor ecosystems. But it is increasingly clear that environmental data does more than simply offer a better view of the planet. This special issue makes a single overarching argument: that we cannot fully understand the current conjuncture in global environmental governance without understanding the platforms, devices, and institutions that comprise environmental data infrastructures. The papers draw together scholarship from political ecology and science and technology studies to demonstrate how data has become a significant site in which contemporary environmental politics are waged and socionatures are materialized. We address: (1) the contested practices of utilizing and maintaining data infrastructures; (2) the ways they are governed and the territorial statecraft they enable; (3) the socionatural materiality they arise within but also produce. The papers in this special issue show that, against its dominant representation, data is material, governed, practiced, and requires praxis. Political ecologists could adopt such an approach to make sense of the emerging ways in which data technologies shape environments and their politics.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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