Egyes mézelő idegenhonos özönfajok értékelése ágazati interjúk alapján
Bibliographic record
Abstract
The studied invasive alien plant species, black locust (Robinia pseudoacacia L.), common milkweed (Asclepias syriaca L.) and the two invasive goldenrod species: the Canadian (Solidago canadensis L.) and the giant goldenrod (Solidago gigantea Ait), are excellent honey producers, and the importance of black locust for the forestry is also significant. However, due to their invasive nature in Central-Europe, they can cause serious damage to nature conservation and in the case of herbaceous species to agriculture. In our research, we conducted interviews with representatives of the four main sectors concerned: nature conservation, beekeeping (apiary), forestry and agriculture at national policy level in 2020. The focus of the research was to explore the four sectors' conflicting points and potential for cooperation related to honey producing invasive plant species. Interview summaries were subjected to qualitative analysis. Our results show that the distribution and trends of the studied species are perceived by the sectors partly in a different way. The most marked conflict between certain sectors is related to black locust. For the conservation sector, black locust is one of the most damaging species, for beekeepers it is the most important honey plant species, and for forest managers it is valuable as wood product, but its invasive character is not recognized by some forestry experts. The mass presence of the common milkweed and the invasive goldenrod species causes high cost for both conservation and agriculture, due to the requirements to control them and the possibility of exclusion from subsidies if they are not controlled. For beekeepers, the common milkweed is steadily losing importance it had a few decades ago, due to a significant reduction in its nectar production capacity as a result of the drought caused by climate change. The importance of the goldenrod lies in the need to feed bee colonies, as it is crucial to replenish their storage with natural pollen, and it is the last significant honey plant of the year. Feedback from sectoral experts suggests that most legislation and subsidies for the species under review is designed to help eradication. However, there are some subsidies that are more conducive to spread. Invasive species are valued differently by the sectors concerned, due to their different interests, but it is encouraging that there is a willingness and example of cooperation. Exploring sectoral views can provide an excellent basis for cross-sectoral discussion and identifying possible solutions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 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; both teacher heads agree on what is shown here.
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".