MétaCan
Menu
Back to cohort

Wajda, Andrzej (1926--)

2018· book-chapter· en· W4234942103 on OpenAlexaff
Maria Ioniță

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPolish Historical and Cultural Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCommunismTrilogyPassionPeacetimePower (physics)Ancient historyHistoryArtPoliticsArt historyPolitical scienceLawArchaeologyPsychology

Abstract

fetched live from OpenAlex

Andrezj Wajda is a Polish film and theater director, best known for his politically engaged films exploring Polish history, and his collaboration with the actor Zbigniew Cybulski. In 1940 Wajda’s father was killed by the Soviets in the Katyn Forest massacre. In 1942 he joined the Polish Resistance, fighting in the Army of the Interior, which had ties to the Polish government in exile in London, rather than to the Soviet Union. He would later translate some of his wartime experiences in his highly acclaimed film trilogy, A Generation (1955), Kanał (1957), and Ashes and Diamonds (1958). The heroes of these movies are young and desperate: in A Generation they are communist partisans. In Kanał they are Jewish fighters during the bloody Warsaw Ghetto uprising. The intensity and passion of their struggle stands in stark contrast to the historical hell they are traversing (Kanał’s descent into the Warsaw sewers is shot to resemble a Dantean inferno). Nowhere is this more evident than in the masterful Ashes and Diamonds, which takes place in the immediate aftermath of the war and details a minor episode in the murky struggle for power between the communist partisans and the Army of the Interior.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.006

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 head0.056
GPT teacher head0.285
Teacher spread0.229 · 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
GenreOther

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

Explore more

Same topicPolish Historical and Cultural StudiesFrench-language works237,207