Examining the relationship between sustainability reporting processes and organizational learning and change
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although there have been a number of publications discussing sustainability reporting (SR) in private and public sectors within the last decades, the number has been quite low when compared to works on non-governmental organizations (NGOs). This research explores this and finds that SR is a key driver for organisational learning and change in NGOs. A combination of descriptive statistics, grounded theory (GT) and inferential statistics was used to analyse the data. The findings show that SR and organisational learning and change share a reciprocal relationship that begins as the driver for learning and extends as change. This reciprocal relationship is repetitive and improves reporting process through enhanced sustainability performance in a mimetic approach. The research shows that SR fosters opportunities for cost and benefit evaluation, the institutionalization of sustainability, transfer of skill and innovation, attitudinal change towards sustainability, stakeholder engagement and ownership, as well as increasing the donor base. The findings further reinforce the contention that SR is influenced by organisational culture, donor behaviour and management decisions. The study also communicates the various lessons learnt from NGOs’ sustainability efforts that other NGOs, private and public sectors can benefit from.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it