Resolving the Technosphere
Bibliographic record
Abstract
Abstract. The global assemblage of human-created buildings, infrastructure, machinery and other artifacts has been called the `technosphere', and plays a major role in the present-day dynamics of the Earth system. It enables the rapid extraction and processing of materials from other spheres, combusts fossil fuels causing climate change, and transports materials and people across the planet surface. It provides a vast range of services to humans, such as supporting the production of food, shelter, long-distance communication, and entertainment. However, Earth system science has been slow to explicitly incorporate the technosphere as an integrated part of its conceptual and quantitative frameworks. Here we propose a refined definition of the technosphere, intended to assist in developing functional integration with other Earth system spheres, and an End-Use Technosphere categorization, EUTEC, that is theoretically aligned with human activities and wellbeing. The formal definition and resolved categorization enable basic attributes of the technosphere to be delineated, including its mass distribution among components and in space, as well as its temporal dynamics. In particular, of the roughly 1 Tt of technosphere mass, we estimate that one third is comprised of residential buildings and one third by the transportation system, both of which we map at one-degree resolution. Moreover, we show that reconstructions of technosphere mass since 1900 follow exponential growth with long-run growth rates of >3 % y-1, consistent with autocatalytic behaviour, allowing it to become an ever-more dominant component of the Earth system. The quantitative understanding of the technosphere remains rudimentary, and is in great need of further work to better integrate it with Earth system science.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".