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Record W2944111519 · doi:10.1177/2053019619848216

A human tragedy? The pace of negative global change exceeds human progress

2019· article· en· W2944111519 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Anthropocene Review · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTragedy (event)AnthropoceneTragedy of the commonsPacePopulation growthUrbanizationPopulationNatural resource economicsDevelopment economicsGlobal warmingClimate changeGeographySocioeconomicsEconomic growthEconomicsEcologyBiologyDemographySociologySocial scienceCommons

Abstract

fetched live from OpenAlex

I analyze changes in the demographic profiles and urbanization rates of 201 countries, and assess 69 global indicators of the human condition, in order to evaluate whether the human population is endangering its persistence and future quality of human life (tragedy of the commons). Encouraging changes in age profiles signal a slowing down in human population growth during the Anthropocene while exponential increases in several economic, education, and health indicators support an optimistic outlook for the future of humanity. But rapid growth by a larger number of negative indicators foretell a global human tragedy plagued by long-term increases in pollution, global warming, waning food production and unparalleled declines in biodiversity. Urgent action is required to avoid further collapse of the Earth System.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.028
GPT teacher head0.317
Teacher spread0.289 · 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