Overcoming plant blindness in science, education, and society
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Plants are amazing organisms. They make up around 80% of all biomass on Earth, play important roles in almost all ecosystems, and support humans and other animals by providing shelter, oxygen, and food. Despite this, many people have a tendency to overlook plants, a phenomenon known as "plant blindness." Here, we explore the reasons behind plant blindness, discuss why some people are relatively unaffected by it, and promote education around plant science to overcome this phenomenon and raise awareness of the importance of plants in the wider community. Summary Many people tend to overlook the importance of plants in the biosphere. This phenomenon is described as "plant blindness," a term proposed 20 years ago to denote the inability of a person to notice plants and/or appreciate their significance. To explore why some people seem immune to plant blindness, we asked plant scientists on Twitter why they became interested in plants. Many replied that their interest developed from early experiences in life or inspiring teachers at school. Others were attracted to the scientific disciplines related to plant science or valued the contribution of plants to global ecosystems and human civilization. Based on these anecdotes and the empirical findings of other researchers, we argue that plants should play a more central role in biological education, from the early years to university and beyond. Furthermore, as plant scientists, we should do our best to raise awareness about the fascinating aspects of plants and their importance in human affairs within the wider community.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it