Finding an academic space: reflexivity among sustainability researchers
Bibliographic record
Abstract
Reflexivity is arguably an important aspect of doing sustainability research. The inter-and transdisciplinary character of sustainability research, as well as its change-oriented agenda, require scholars to reflect on their role as researchers, their research focus and methodology, and its relation to academia and society. Using focus groups with 15 researchers at different stages in their academic career, we investigate three forms of reflexivity, i.e., personal, functional, and disciplinary, for sustainability researchers connected to the LUCID (Lund University Centre of Excellence for the Integration of the Social and Natural Dimensions of Sustainability) program experience. We further study similarities and differences in how the researchers experience reflexivity connected to interdisciplinary and transdisciplinary approaches. We find that sustainability researchers experience all three forms of reflexivity. In particular, they are highly reflexive about how research on sustainability issues is dependent on theoretical pluralism; how research can contribute to the transformation of society; and how they, as inter-and transdisciplinary researchers, can construct a space for themselves within the academic system. We also find that transdisciplinary approaches make scholars add a layer of reflexivity to the three categories studied, concerning collaboration beyond academia. Finally, we find that reflexivity about these issues seems to be crucial for how sustainability researchers construct a space for themselves within the academic system. PhD graduates from the LUCID program are deeply reflexive about the function of academic boundaries. It is this awareness that enables them to construct an academic identity entirely beyond boundaries. This result has important implications for PhD programs focused toward sustainability issues, in terms of a need to provide opportunities for PhD students to develop reflexivity.
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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 | 0.153 | 0.172 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.020 | 0.063 |
| Scholarly communication | 0.033 | 0.026 |
| Open science | 0.005 | 0.035 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".