Psychosocial factors influencing the experience of sustainability professionals
Bibliographic record
Abstract
Purpose The purpose of this study is to gain insight into psychosocial factors influencing sustainability professionals in their work to lead by influencing and improving pro-environmental decision-making in their organisations and to increase understanding of psychosocial factors that affect their effectiveness in achieving desired results. Design/methodology/approach Using Interpretative Phenomenological Analysis as a framework, the study enquires into the lived experience of six research subjects. The participants are sustainability professionals and leaders from the UK and Canada. The primary data source is semi-structured interviews, analysed with micro-discourse analysis. Findings Key psychosocial factors involved in participants’ experience are identified, specifically psychological threat-coping strategies, psychological needs, motivation and vitality, finding complex interactions between them. Tensions and trade-offs between competency, relatedness and autonomy needs and coping strategies such as suppression of negative emotion and “deep green” identity are modelled in diagrams to show the dynamics. How these tensions are negotiated has implications for psychological well-being and effectiveness. Practical/implications The concepts and models presented in this paper may be of practical use to sustainability professionals, environmentalists and organisation leaders, for example, in identifying interventions to develop inner resources, support authentic and effective action and disrupt maladaptive responses to ecological crisis. Originality/value The study contributes insight to understanding of underlying processes shaping environmental cognition and behaviour, particularly in relation to psychological threat-coping strategies and interacting factors. With a transdisciplinary approach, the methodology enables nuanced interpretation of complex phenomena to be generated.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".