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Record W3004284964 · doi:10.46692/9781529202175.002

Renewable Resource Scarcity, Conflicts and Migration

2020· other· en· W3004284964 on OpenAlexaboutno aff
Tobias Ide

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsScarcityNatural resource economicsResource (disambiguation)Resource scarcityRenewable resourceRenewable energyBusinessEnvironmental economicsEconomicsEcologyComputer scienceBiologyMicroeconomics

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.027
GPT teacher head0.191
Teacher spread0.163 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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