Bibliographic record
Abstract
Abstract This article builds on Carolan's three natures scheme, where he distinguishes between the strata of ‘nature’, nature and Nature, by overlaying his previous framework with further analytic distinctions. Doing this, the authors argue, adds an important layer of analytical and conceptual robustness that his earlier scheme lacks. After building on this framework, attention turns to the phenomena of climate change. A selection of agrifood studies on this subject is used to help illustrate the utility of the revised model. The literatures reviewed involve the following: those looking at attitudes among farmers toward climate change; the bark beetle outbreaks in British Columbia; and food regimes. With this move the authors seek to illustrate the explanatory and descriptive utility of the revised model, specifically in its ability to provide a sustained defence of a type of realism that relational social theorists implicitly ascribe to. They also show how their conceptual labours – and the ecologically embedded relational realism it brings to the fore – can help further inform the aforementioned literatures by highlighting some of their conceptual and analytic blind spots.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.047 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".