Bibliographic record
Abstract
Student composed text panel: E.J. Howorth (Canadian, b. 1943)Drip and Dip, 2013ScreenprintUND Art Collections: Art & Design Study CollectionOil/Water Exchange Portfolio E.J. “Ted” Howorth is a Canadian-born artist, who is currently employed by the University of Manitoba, where he graduated in 1969. In 1995, he was appointed to the Royal Canadian Academy of Arts. Howorth now lectures full-time in printmaking and drawing. Howorth explained that when creating this print, he was focused on natural disasters caused by man. The result was a piece that brought light to the issue and served as an escape: the hot water brings out the oils in coffee that give it flavor. To the viewer, this artwork might symbolize the escape that a simple coffee break can provide. Artist Statement: "When making this print, I had a couple of ideas in mind. On my initial research, I kept relating to all the natural disasters caused by man and so in the end of I tried to escape all of that and find a more positive note in the bringing together of these two materials. So my "oil & water" mix is the wonderful flavor of oils from roasted coffee beans when released by boiling water. This print was a also a chance to try and work directly on the screen simulating light reflecting on water by simple reduction technique."
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.737 | 0.357 |
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".