Bibliographic record
Abstract
According to Michael Zarin, Director of Government Relations with Vestas Wind Systems, there is nothing “alternative” about wind power anymore (Biello, 2010). After all, wind generation is the most cost-effective option for new grid-connected power in markets like Mexico, South Africa, New Zealand, China, Turkey, Canada, and the United States (Renewable Energy Policy Network [REN21], 2016). At 433 GW of cumulatively installed capacity in 2015 worldwide, more than half was added in the past 5 years (REN21, 2016). This technology may be used by individuals, communities, and utilities. It can be grid-connected or off- grid, and be used onshore or offshore. This chapter examines the influences and evolution of the Danish wind transition, highlighting how ingenuity and often less-obvious incremental advances produced a world-class industry. It reveals how citizens can be important catalysts of energy system change. The case also indicates that innovations can emerge in practices and policy, not just technology, science or industry. Denmark is a cultural and traditional technology leader for modern wind power. This country of roughly 5.6 million people and GDP of approximately $65 billion in 2016 (ppp) (Central Intelligence Agency [CIA], n.d.) is where today’s dominant, wind turbine design was established and where state-of-the art wind technology testing centers are based. It is also the site of the first, commercial-scale offshore wind farm, built in 1991. Denmark has a world-class hub for wind energy technology (Megavind, 2013; State of Green, 2015; Renewable Energy World, 2016). Top-ranked companies like Vestas, LM Wind Power, Siemens Wind Power, A2SEA, and MHI Vestas Offshore Wind are among those that base core parts of their global operations in Denmark. A close network of wind engineers and their professional affiliates drives the industry, which includes ancillary services and subcomponent supplies. Wind energy technology also represents one of Denmark’s top-ranked exports (United Nations Comtrade, n.d.). Currently, Denmark has more wind power capacity per person than does any other country in the world (REN21, 2017). This Northern European nation is on track to derive 50% of its electricity from wind power by 2020.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 0.013 |
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".