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Record W3172151173 · doi:10.14324/111.9781787357167

Transforming Early Childhood in England: Towards a Democratic Education

2020· book· en· W3172151173 on OpenAlexfundno aff

Bibliographic record

VenueUCL Press eBooks · 2020
Typebook
Languageen
FieldEngineering
TopicArchitecture, Modernity, and Design
Canadian institutionsnot available
FundersUniversity of BrightonUniversity of CambridgeUniversité du Québec à MontréalUniversity of Pennsylvania
KeywordsComputer scienceSociology

Abstract

fetched live from OpenAlex

Expanding Fields of Architectural Discourse and Practice presents a selection of essays, architectural experiments and works that explore the diversity within the fields of contemporary architectural practice and discourse. Specific in this selection is the question of how and why architecture can and should manifest in a critical and reflective capacity, as well as to examine how the discipline currently resonates with contemporary art practice. It does so by reflecting on the first 10 years of the architectural journal, P.E.A.R. (2009 to 2019). The volume argues that the initial aims of the journal – to explore and celebrate the myriad forms through which architecture can exist – are now more relevant than ever to contemporary architectural discourse and practice.

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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.149
Threshold uncertainty score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0180.018
Scholarly communication0.0120.008
Open science0.0010.011
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0130.002

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 head0.016
GPT teacher head0.213
Teacher spread0.197 · 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 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

Citations2
Published2020
Admission routes1
Has abstractyes

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