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Record W7041223555

KID ARCHITECTURE

2018· article· en· W7041223555 on OpenAlexaboutno aff

Bibliographic record

VenueOpenSIUC (Southern Illinois University Carbondale) · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Process (computing)NucleofectionFrame (networking)Population
DOInot available

Abstract

fetched live from OpenAlex

The kid architecture program was developed thirty years ago to introduce young people to the design of the built environment. The one-week camps structured for three different learning levels, grades 4th–6th, middle school and high school have been conducted in various locations internationally to include the Smithsonian, The National Building Museum Washington D.C., Canada and China. The camps have received national and regional awards for the broad breath of hands-on activities and implementation of technology. The ten objectives for kid architecture endeavor to develop an understanding of the following: • Why buildings look the way they do • Why building stand up • What architects and designers do? • Design drawing as a problem solving tool/method • The use of the design process as employed by architects • How a building is designed, constructed, used and reused • Construction materials used in buildings • How and why people “define” space 6 • The use of computer graphics, animation and Computer-aided design • Participation in the design of the built environment The philosophic foundations that kid architecture is built upon is the assumption that those who are exposed early to architectural design will have a different conceptual base from which to formulate more complex and differential ideas about the built environment. Architecture Camps’ personnel believe this cognitive skill is as basic to a young person in the modern world as knowing left from right or discriminating the letters “b” from “d.” Future advances in the conceptualization of buildings, cities, and personal living spaces will be made by people who are deeply aware of the built environment.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.887
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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.032
GPT teacher head0.209
Teacher spread0.177 · 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 designNot applicable
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

Citations0
Published2018
Admission routes1
Has abstractyes

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