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Record W4387465306 · doi:10.17721/2518-1270.2023.71.22

NEW BOOK ON VISUAL ANTHROPOLOGY AND DIASPORA EPISTOLARY. BOOK REVIEW: Mayerchyk M., Pogosjan J., Yesypenko D. Lena and Thomas Gushul: Life in Front and Behind the Camera. Vol.1–2. Edmonton: Peter and Doris Kule Centre for Ukrainian and Canadian Folklore, 2023. 136 + 212 p.

2023· article· en· W4387465306 on OpenAlexaboutno aff
Maryna HRYMYCH

Bibliographic record

VenueEthnic History of European Nations · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicDiverse Scientific Research in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianFolkloreFront (military)StudioArt historyDiasporaHistoryMedia studiesVisual artsArtSociologyGender studiesArchaeologyGeography

Abstract

fetched live from OpenAlex

The two-volume book by the authors team – Dr. Yelena Poghosyan, Dr. Maria Mayerchyk and Dmytro Osypenko, «Lena and Thomas Gushul: Life in front of and behind the camera», which was just published in Edmonton (Canada), was reviewed. This is a solid project on the history of Ukrainian diasporic visual culture and at the same time on Ukrainian diasporic epistolary, which was carried out at the Doris and Peter Kule Center for Ukrainian and Canadian Folklore (University of Alberta, Canada). The peer-reviewed work concerns the beginning and the first half of the 20th century, highlighting the life and work of the couple Olena and Thomas Gushul, who were of Ukrainian origin. Having their photo studios in two mining towns in southwestern Canada, they managed to break out of the narrow framework of the photo business of that time and become photo artists, enriching the history of Canadian and Ukrainian diasporic visual culture with their works. The authors included in their book and analyzed a rich family epistolary, which illuminates the life of the Ukrainian working and intellectual environment of the first decades of the 20th century.

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)0.002
metaresearch head score (Gemma)0.001
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: Review · Consensus signal: none
Teacher disagreement score0.482
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.288
Teacher spread0.259 · 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
GenreReview

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
Published2023
Admission routes1
Has abstractyes

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