Estimating the potential of achieving self-reliance by rooftop gardening in Chiayi city, Taiwan
Bibliographic record
Abstract
More than half of the global population has chosen to live in urban areas than in rural areas. This results in issues on sustainable food provision in urban areas. Transporting vegetables and fruits from the countryside to the city while keeping them fresh consumes energy and causes loss. Given the cost, growing food in and around cities has never been a new thing. However, only recently, growing food on rooftops on a business scale to achieve self-reliance has increasingly gained attention. With current technological advances in horticulture and agriculture, it has become more likely to secure food provision by cultivating on urban rooftops. Only a few business scale cases reported in high-income societies with a high-density population or experiencing snowing winter can afford and justify the choice of such a high input as well as a high-yield cultivating system. In Taiwan, with a warm winter, it may be more feasible to apply this system because less energy input is required to achieve the same yield as compared to that required in places in temperate climates. By estimating the potential of a high-density city to achieve self-reliance through rooftop growing systems, decision-makers can have more insight into how the idea can be promoted. As of end 2016, Chiayi city has the second largest population density after the capital city. Thus, this research aims at assessing the potential to achieve self-reliance by growing food on rooftops in Chiayi. It analyzes the yields of four types of rooftop cultivating systems and estimates the production and consumption by using these systems on three types of rooftops in different land uses, namely commercial, educational and residential. The result shows that the best scenario for achieving self-reliance is the rooftop hydroponic greenhouse model operating at the commercial scale although this is not sustainable or practical for general households in Chiayi City.
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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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".