Conceptual lenses to bring into focus the blurred and unpack the entangled
Bibliographic record
Abstract
Concepts have navigational consequences, guiding towards understanding and social practices that decrease danger, or misdirecting into assumptions that problems are being solved when worsening and that nature can be socially reconstructed at will. This article showed there has been a mismatch between natural science conclusions of what is needed to mitigate anthropogenic climate change and conceptions by polluters and many social scientists. It confirmed that natural science is needed to ground social science analyses of environmental problems. Some social theory previously made a cultural turn and recently a material turn, replacing culture/nature dualism with antidualist hybrids. The article demonstrated that much of environmental sociology has not zigzagged like that, instead consistently focussing on the interpenetration of social constructions and nature’s constructions. Rather than one-size-fits-all conceptions that indiscriminately interpret everything as hybrids, it proposed nuanced conceptions where hybridisation is variable and unpacked conflated conceptions. It argued that sociotechnological innovation has led to the internalisation of primal nature’s dynamics previously external to societies and unleashed primal nature. This results in intensified interaction between social constructions and nature’s constructions, and nature becoming a medium carrying social relations. Premature predictions of emancipatory catastrophism were shown to result from mistaking discourse for action.
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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.006 | 0.063 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 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".