Authors of misfortune: interpretation and expertise in a model disaster
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
Abstract Since 2001, beetles have killed two‐thirds of the pine trees in British Columbia, Canada, decimating the predominant commercial tree species in one of the world's largest timber economies. Attempts to construct and circulate computer models of the infestation and its aftermaths, however, have obscured destabilizing changes across state institutions for environmental research. Juxtaposing literary conceptualizations of distributed authorship with ethnographic critiques of technoscientific bureaucracy, this article examines how the proliferation of computer models in contemporary resource planning institutions has altered the ways experts participate in and sanction interpretive communities. The dynamic conceptualizations of authorship produced through these exchanges challenge existing portraits of anticipatory governance, an emergent mode of administration that often relies on models for procedural implementation and narrative framing even as it circumscribes modellers’ voices to specific moments of interpretation and critique. While modellers make claims on distant futures to provoke discussion among diverse actors, later interpreters may highlight a model's apparent precision or its radical uncertainties to defer criticisms of problematic interventions and government restructuring. Such modes of attribution have deepened many scientists’ sense of estrangement from the interpretive communities their models help to engender.
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 | 0.001 |
| 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