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Record W4295197024 · doi:10.1177/09596836221121777

Holocene desertification, traditional ecological knowledge, and human resilience in the eastern Gobi Desert, Mongolia

2022· article· en· W4295197024 on OpenAlexaff
Arlene M. Rosen, Lisa Janz, Dashzeveg Bukhchuluun, Davaakhuu Odsuren

Bibliographic record

VenueThe Holocene · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsHoloceneDesertificationGeographyAridWetlandHabitatEcologyNatural (archaeology)Ephemeral keyPsychological resilienceRange (aeronautics)PastoralismPhysical geographyArchaeologyLivestockBiology

Abstract

fetched live from OpenAlex

Dryland regions are particularly challenging for human survival over the course of deep time. This is true for institutionally complex communities as well as small-scale societies that have existed in semi-arid regions throughout the Holocene. This paper examines some of the successful strategies employed by small-scale mobile communities which enhanced their ability to thrive in drylands over the course of thousands of years. Small-scale societies living in drylands must rely on the transmission of Traditional Ecological Knowledge across generations. Some of this knowledge relates to the availability and use of wetlands and other more ephemeral water sources, the exploitation of a diverse range of resources, and the potential for natural storage of food resources as a buffer against regularly occurring drought years in these regions. We compare this understanding with our environmental archeological findings at the Mid-Holocene site of Zaraa Uul in the eastern Gobi Desert of Mongolia. At the site of Zaraa Uul, we show how hunter-gatherer groups returned to a campsite near the edge of a wetland environment over the course of at least two phases during the Mid-Holocene. Here they took advantage of a greater diversity of animal species and plants, including small-grained-grasses and sedges, which could enhance their caloric intake and increase the potential for storable commodities which could be collected as needed from their natural habitat.

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)0.001
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 score0.055
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.034
GPT teacher head0.252
Teacher spread0.218 · 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; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations12
Published2022
Admission routes1
Has abstractyes

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