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Record W1491476789

Inventory of manors – future of the past

2011· article· en· W1491476789 on OpenAlexaboutno aff
Olev Suuder

Bibliographic record

VenueBaltic Journal of Art History · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsHindsight biasHistoryQuarter (Canadian coin)Period (music)ArchitectureRomancePoint (geometry)AestheticsArchaeologyLiteratureArtPsychology
DOInot available

Abstract

fetched live from OpenAlex

The future of the past – this was the philosophical point of view used by Helmi Uprus decades ago in interpreting manorial architecture, when the first summaries were compiled on the inventories of manors.1 The survival and preservation of cultural heritage involve topics which occasionally become clear only after a certain period of time, in hindsight, and where the future can sometimes be quite contradictory because of radical changes in society. By the mid-1970s, the temporal distance had become sufficient to tackle the topic of manors as cultural memory in real time and place, i.e. it was possible to seek out values that had been neglected for some reason and thus forgotten. Various painful aspects related to manors had lost their edge and manor houses had become a topic of architectural history. By the last quarter of the 20th century, about three generations had passed since manorial life ended2. During that time, emotions had cooled and ownership relations had changed. Manors now seemed like a distant romantic world, where our ancestors were busy as well, although mostly in the role of coachmen and cooks. World War I and the subsequent revolutions disrupted the continuity of manorial life, both politically and economically, and caused chaos in the way of life. The newly established Republic of Estonia and the

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.478
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.100
GPT teacher head0.191
Teacher spread0.091 · 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
Published2011
Admission routes1
Has abstractyes

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