Social accountability 8000: A quarter century review
Bibliographic record
Abstract
Social Accountability 8000 (SA8000) is the most prominent certification-based standard in the field of working conditions and sustainability. Twenty-five years after the release of the standard, a literature review is needed to highlight the knowledge in the field of SA8000 and identify the impacts of its adoption on companies, employees, supply chains and stakeholders. To this end, this study aims to summarise the findings in the literature focusing on SA8000 and evolution of SA8000 research by providing a review based on the most influential scientific articles published between 1997 and 2022. A 10-step method that combines the best methodological practices for conducting a literature review is used for the analysis, ensuring the study's transparency and reproducibility. The following seven research areas emerged from the SA8000 literature: standard structure, purpose and diffusion; standard comparison and integrated management system; human resources management and working conditions; supply chain management; sustainability disclosure and reporting; drivers and barriers to SA8000 adoption; and performance and outcomes. The contributions included in each area were analysed, and open questions were identified. An agenda for future research is presented.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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".