The appropriated carrying capacity of tomato production : comparing the ecological footprints of hydroponic greenhouse and mechanized field operations
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
Agribusiness advocates claim that modern agro-technology has led to higher per hectare yields. In particular, hydroponic greenhouse agriculture is advanced as a new and particularly productive approach to high output farming. This may contribute to the belief that agricultural land can be urbanized because human ingenuity is seemingly developing substitutes for the lost soil. This thesis challenges this assumption by examining agricultural technology from an ecological perspective. It uses the concept of the ecological footprint (or appropriated carrying capacity) to compare the productivity of hydroponic agriculture with that of conventional open field operations. I assess and compare the biophysical inputs required by these operations to produce 1000 tonnes of tomatoes. These figures are then translated into corresponding land areas (in various categories) necessary to produce the required biophysical inputs. In contrast to common belief, hydroponic operations require 14 – 21 times more land than conventional open field operations to produce the same output (including the land directly occupied by the farms). This case study demonstrates the merits of appropriated carrying capacity analysis for assessing progress toward sustainability. It shows that hydroponic agriculture is a prime example of apparent economic success which is, in fact, ecologically unsustainable. There is no reason for confidence that we can pave over our agricultural lands just yet! Finally, this study demonstrates that the apparent yields of hydroponic greenhouse agriculture are partially a reflection of under priced resource inputs, a form of subsidy which is not sustainable.
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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 | 0.001 | 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