Bibliographic record
Abstract
Science has lots of developed many means to measure and monitor economic and social phenomena, processes, and environmental conditions; now we want to measure sustainability. The first step is to make an exact definition of sustainability. The definition made by the Brundtland Commission defines it in terms of needs and limitations. Sustainable growth is only possible with harmonic development. Harmonic development is based on three ideas: social forms, economical level, and carrying capacity of a natural system. Economical efficiency determines social relationships, and these are limited by the carrying capacity of natural systems. For the sake of my research I analyzed mainstream scientific authorities. The Canadian National Round Table on the Environment and the Economy created six sustainability indicators. A US company called Sustainable Measures defined ten measurable interaction factors for sustainable development. The Global Report Initiative used triple bottom line in the assessment. In my thesis I survey and compare these methods, and make a proposal regarding practicable routines for European companies. Keywords: sustainability, sustainability indicators, measurement
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 | 0.032 | 0.124 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.015 | 0.036 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".