Bibliographic record
Abstract
Introduction Renewable resources such as water, soil and forests regenerate after extraction. The day when human consumption exceeds global nature's regeneration capacity in a given year is called ‘earth overshoot day’. In an ideal world, this day would be on 31 December of the same year or later. In the year 2000, however, earth overshoot day was on 23 September, and ten years later, humanity's annual budget of renewable resource use had already expired on 9 August. The 2018 earth overshoot day was on 1 August (Earth Overshoot Day Network, 2018). This indicator is, of course, broad, but it demonstrates that the world's renewable resources face some worrisome degradation trends. As illustrated by Figure 2.1, the amount of arable land and available freshwater resources per capita, and the global forest area, have all been in decline in the past 25 years. The main drivers of this increasing resource scarcity are rising levels of consumption (especially by the developed countries and emerging global middle classes) and population growth. Unequal access to natural resources (and related services) further plays a role by allowing for excessive overconsumption of the haves and by stimulating desperate overextraction by the havenots. Climate change, itself a product of human-induced CO 2 releases into the earth's atmosphere (see Figure 2.1), will further aggravate the situation, for instance, due to more frequent droughts and a rising sea level (see Chapter 4). In the face of growing worldwide scarcity, access to renewable resources remains highly unequal within and between states. This is due to a number of factors. First, climatological, physical and geographical factors cause an unequal distribution of natural resources. Canada, for instance, has much more renewable freshwater (2.850 billion cubic metres) per year than Libya (one billion cubic metres). Second, some countries and regions are more effective (though not necessarily more sustainable) in managing their existing resources, for instance through dams, land-use planning, groundwater exploitation and demand management. Third, purchasing power is an important determinant of resource access. Rich states can import virtual water and land in the form of food or desalinate sea water, while poor ones have more difficulties in doing so.
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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) | 0.000 | 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) | 0.006 | 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 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".