The Sustainable Development Goals: A Tipping Point for Impact Measurement?
Bibliographic record
Abstract
This article proposes a holistic framework of integrated social accounting that could be adopted by all types of organizations in the social economy, as well as in other sectors. The impetus for this derives from the popularity of the sustainable development goals (SDGs) and the broadening of collective impact thinking. The article advances a model of integrated social accounting that brings together four dimensions: 1) resources/capitals, 2) value creation/destruction, 3) internal systems and processes, and 4) organizational learning, growth, and innovation. Organizations using this model focus on the implications of their activities through the lens of the SDGs, looking both internally and externally.Cet article propose un cadre global de comptabilité sociale intégrée qui pourrait être adopté par les organisations de l’économie sociale, ainsi que dans d’autres secteurs. Cela découle de la popularité des objectifs de développement durable (ODD) et de l’élargissement de la réflexion collective en matière d’impact. L’article avance un modèle de comptabilité sociale intégrée qui regroupe quatre dimensions : 1) ressources / capitaux, 2) création / destruction de valeur, 3) systèmes et processus internes et 4) apprentissage organisationnel, croissance et innovation. Les organisations qui utilisent ce modèle se concentrent sur les implications de leurs activités dans l’optique des ODD, en cherchant à la fois en interne et en externe.
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 | 0.045 | 0.100 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.015 | 0.041 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.004 | 0.007 |
| 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".