Developing a Glossary of People-Focused Terms Related to Rangelands and Grasslands
Bibliographic record
Abstract
Excellent glossaries on rangelands and grasslands have been developed by the Society for Range Management (SRM), the International Grassland Congress (IGC) and the International Rangeland Congress (IRC). However, these are largely confined to biophysical and technical terminology and contain very few concepts referring to social, institutional and policy aspects of using rangelands and grasslands. After the 10th IRC in Saskatoon, Canada, in 2016, an informal group started to develop a glossary of such “people-focused” terms. The short and non-academic definitions are meant to improve communication and understanding by users/practitioners in rangeland and grassland management, policymakers, teachers, students, journalists and the general public. The glossary focuses on terms in common international use in rangeland management and includes terminology referring to rangelands/grasslands users (e.g. pastoralists, agropastoralists, hunters and gatherers) and to how they organise the use and management of rangeland resources (e.g. common property rights, resource access rights, herding contracts, transhumance and other forms of mobility). More general terms in social sciences are not included, as the debates about their meanings are well covered in the conventional social science literature. Thus far, the glossary is in English only. It is hoped that people working on rangelands and pastoralism in other countries will translate it into other languages and adapt it with area- and language-specific terminology. The definitions in the glossary are intended to fill an existing gap relatively quickly. Previous experience of the SRM, IRC and IGC showed that developing a comprehensive glossary takes several years. The current version of the glossary will doubtless be revised when a more systematic effort is made to define socio-institutional terms related to rangelands and grasslands. In any case, further revisions will be made as concepts evolve and new ones arise, as was the case with the technical glossaries of the SRM, IGC and IRC.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.014 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.064 | 0.035 |
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".