Jeff Wall Catalogue Raisonné 2005–2021
Bibliographic record
Abstract
Since 2005 the internationally renowned Canadian artist Jeff Wall (born 1946) produced seventy-three pictures. This catalogue raisonné documents these photographs by the artist, listed with the catalogue raisonné numbers 120 to 192. During the past fifteen years, the literature and scholarship on the artist’s photographic pictures and their exhibition around the globe has proliferated. Wall’s photographs from this period enhance his already substantial reputation as both a maker and a theoretician, one of the most articulate voices on art, culture, and photography this century. Jeff Wall Catalogue Raisonné 2005–2021 is a second volume of the systematic compilation of information and materials on the artist's photographs, including technical data and information of each artwork’s history. My role as author and editor included writing the introductory essay, researching the catalogue raisonné, preparing the comprehensive exhibition history including complete information on all works displayed in each exhibition, the bibliography, the biography, as well as the transcription and editing of conversations the artist recorded on video in 2015 and 2018.This second volume of the catalogue raisonné, published in association with Yale University Press, is entirely new scholarship and an important resource for a future generation of art historians.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.290 | 0.170 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".