AESTHETIC AND BIOLOGICAL PERCEPTIONS OF SUCCESSIONAL FOREST
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
ABSTRACT Five Alberta Communities were chosen to represent five separate community types—agricultural, oil extraction, two forestry and urban professional. Each participant in the research was exposed to a reasoned argument supporting either forest harvest or forest preservation. Afterwards, each participant inspected 8 large numbered colour prints showing forest landscapes in different stages of development. Ratings were made on two scales. One measured perception of what the forest provides the perceiver for good or ill, the other—perception of beauty. We found a consistent order of preference that was independent of type of community and type of preparatory argument. A second investigation measured how alternative policies of sustainable forest management might influence forest perceptions. Using the same scales and a subset of the four colour prints, ratings of forest landscapes were found to confirm the first results: landscape preferences were found to be preconceived and not changed by type of forest management responsible for the forest. This outcome is consistent with the possibility that perceptions of successional stages of forest occur as an expression of human gene/vegetation interactions that are minimally affected by learning.
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) | 0.000 | 0.000 |
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