<b>Future shock in forestry</b> Where have we come from; where are we going; is there a "right way" to manage forests? Lessons from Thoreau, Leopold, Toffler, Botkin and Nature
Bibliographic record
Abstract
Future shock (Toffler 1970) occurs when the rate of change in society exceeds the willingness or ability of individuals and institutions to adapt to the change. The rapid increase in human population and change in expectations of forestry over the past 40 years has created future shock in our profession. A similar situation has developed in the social and biophysical sciences. Future shock is threatening to divert the evolution of forestry from its path towards site-specific, multi-value social forestry that respects both ecological and biological diversity. It is doing so by forcing change ahead of our knowledge and experience of the outcomes of the change. This is threatening to replace the site-specific, professional decision making that respects nature and social values and is needed to achieve a sustainable relationship between humans and forests, by rigid, administrative, regulation-based forestry. It may even encourage a return to what in reality can become exploitative forestry under the guise of aesthetics, beauty and care for the environment. Forestry has always been changing as society's expectations, needs and desires with respect to forests have changed. This is appropriate and should continue, but it should be the right change—change that respects the ecology and sociology of the desired new balance of values. This new balance includes, as it should, a variety of non-traditional values, but these should be additive to, rather than a replacement for, such important social values as employment, wood products and wealth creation. There is a variety of new paradigms and new institutional arrangements that could guide this change in forestry, but first there needs to be a clear statement of a desired forest future. Lacking the 100-year experience of the outcomes of these new paradigms, we need to develop and use credible, ecologically based, forest ecosystem management models based on both experience and knowledge to help guide the evolution of forestry towards the desired goal. Appropriately trained professional foresters should remain the foundation for the design and implementation of forestry that achieves the desired new balance of values, while a much wider representation of social interests will be involved in setting the new forestry goals. There is merit in listening to the words and philosophies of the great thinkers on forestry and conservation issues. Important lessons can be learned. However, there has been a pervasive misinterpretation of many of the wise thoughts of writers like Thoreau and Leopold. When carefully revisited, their wisdom supports the balanced view of forestry and nature that appears to be the only way forward towards the future that we think our grandchildren and their grandchildren will want. Key words: future shock, development of forestry, respect for nature, paradigms for forestry, forecasting the future, Leopold, Thoreau, Botkin
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".