Answering the call for #<scp>GenerationRestoration</scp>: The Special Feature from the Society for Ecological Restoration and British Ecological Society to meet the challenges under the United Nations Decade on Ecosystem Restoration
Bibliographic record
Abstract
The United Nations Decade on Ecosystem Restoration (https://www.decadeonrestoration.org/) offers hope in a particularly turbulent time in human history. We write this in the throes of the COVID-19 pandemic that has disrupted the entire planet's social systems exacerbated by increasing totalitarianism, kakistocracy, racism, sexism, homophobia, and transphobia. Hope seems in short supply. A practical path to build on hope might seem even scarcer. But letting the current state of the world bake into failure, ennui, and nihilism is not inevitable. In fact, restoration ecology was born of a failure to protect the environment and the socioecological systems as a whole. It has at the heart of its ethos an inherent optimism—that though we have damaged the environment, people also have the power and ability to repair that damage and imagine ecosystems of the future. It was—and is—one path out of the mess we have made. What we can achieve still depends on a seeming blizzard of “ifs”: it all depends on if we are successful in developing the technical, scientific, and engineering devices and engaging in the social, economic, policy, and governance processes. Some of this is achieved at the international and national level but the rise of economic systems that leave environmental damage and ecosystem services off of the ledgers, and the antipathy of too many citizens and political parties to grand plans, mean that the nurturing of restoration ecology is going to depend on making small efforts that are not only beautiful and functional but relevant to people. We launched the first joint project of the Society for Ecological Restoration and British Ecological Society in the spirit of cooperating to put our best minds and best efforts to the task of accomplishing the goals of the United Nations Decade on Ecosystem Restoration. This Special Feature runs across eight journals (Restoration Ecology, Ecological Solutions and Evidence, Functional Ecology, Journal of Animal Ecology, Journal of Applied Ecology, Journal of Ecology, Methods in Ecology and Evolution, and People and Nature) and readers will see the initial pulse of articles over the next year or more. We will not stop here. More initiatives are on a brighter horizon. As 2021 dawns and the Decade on Ecosystem Restoration breaks through the acidic fog of 2020, hundreds of restoration ecologists have answered the call. Not just our call for papers. The call to hope—and to make that hope into socioecological reality via #GenerationRestoration.
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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.226 | 0.142 |
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".