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Record W2131771374 · doi:10.3390/su5114908

History Made for Tomorrow: Hakka Tulou

2013· article· en· W2131771374 on OpenAlexaboutno aff
Richard Yelland

Bibliographic record

VenueSustainability · 2013
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsnot available
FundersWest Virginia UniversityNational Science Foundation
KeywordsRammed earthSustainabilityChinaEcological footprintEngineeringSustainable developmentCivil engineeringSociologyGeographyPolitical scienceArchaeologyEcologyLaw

Abstract

fetched live from OpenAlex

The documentary film, History Made for Tomorrow: Hakka Tulou was an October 2010 release by History Channel International. This film is an in-depth study on the green building techniques and sustainable lifestyle of the Hakka people of Southern China with a focus on the ancient Tulou rammed earth structures. The television program follows West Virginia University research professor, Ruifeng Liang, as he initiates scientific studies to back claims that the rammed earth Tulou structures are “the greenest buildings in the world”, and Canadian architect, Jorg Ostrowski, of Autonomous Sustainable Housing Inc., who has been researching the ecological footprint of Hakka communities since August 2007, to promote them as “eco-villages” of best practices for planet Earth’s sustainability. The author is credited as Director, Writer, and Producer of this film. This paper is based on the script of the production.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.075
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.001
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0750.010

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 head0.010
GPT teacher head0.204
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2013
Admission routes1
Has abstractyes

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