Sustainability reporting – a systematic review of various dimensions, theoretical and methodological underpinnings
Bibliographic record
Abstract
Purpose This review aims to summarize the extent to which sustainability dimensions are covered in the selected qualitative literature, the theoretical and ontological underpinnings that have informed sustainability research and the qualitative methodologies used in that literature. Design/methodology/approach This study uses a systematic review to examine prior empirical studies in sustainability reporting between 2000 and 2021. Findings This review contributes to sustainability research by identifying unexplored and underexplored areas for future studies, such as Indigenous people’s rights, employee health and safety practice, product responsibility, gender and leadership diversity. Institutional and stakeholder theories are widely used in the selected literature, whereas moral legitimacy remains underexplored. The authors suggest that ethnographic and historical research will increase the richness of academic research findings on sustainability reporting. Research limitations/implications This review is limited to qualitative studies only because its richness allows researchers to apply various methodological and theoretical approaches to understand engagement in sustainability reporting practice. Originality/value This review follows a novel approach of bringing the selected studies’ scopes, theories and methodologies together. This approach permits researchers to formulate a research question coherently using a logical framework for a research problem.
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 | 0.039 | 0.130 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.025 | 0.024 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".