Bibliographic record
Abstract
This interview was conducted over email between Kelly Hammond and Micki McCoy in parallel with McCoy’s article in Yishu: Journal of Contemporary Chinese Art(forthcoming January/February 2009) on the depiction of ethnic minorities in propaganda posters in the People’s Republic of China made prior to the Opening and Reform. The posters can be seen as historical predecessors for contemporary official depictions of ethnic diversity such as that seen at the 2008 Olympics Opening Ceremonies. Yet this imagery is distinct from current commercial visualizations of ethnicity and nationality in the PRC, as described in the interview below regarding Hammond’s participation in a Chinese Pepsi commercial. McCoy: How were you approached to do this? Hammond: I was approached by one of the owners of Fubar, the “foreigner bar” in Urumchi. I’d been to Fubar on numerous occasions and knew the Irish manager and part owner. I received a text message from one of the American graduate students who was also studying Uyghur at Xinjiang Normal University (新疆师范大学) alerting me that they were looking for people to participate in the ad and that the salary for two days work would easily cover my rent for a month. Essentially, the casting director from Shanghai (he was originally from Hong Kong, went to the Vancouver Film School, and is now based in Shanghai—he spoke Cantonese and English wonderfully, but very little Mandarin) got in touch with a few foreigners who were well connected to the different expat communities in the city. For instance, the casting director somehow managed to get in touch with a very well known Kazakhstani student who was studying Mandarin at Xinjiang Agricultural University (新疆农业大学) and who was connected to pretty well the entire Kazakhstani student population studying in Urumchi. He also managed to get in touch with one of the Pakistani students, who are part of a pre-med program offered in English at Xinjiang Medical University (新疆医科大学), which is specifically designed for Pakistani nationals hoping to qualify for medical school abroad. From there, the casting director left it up to these local liaisons he had recruited to spread the word within the different expat communities living in Urumchi about the Pepsi shoot.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.109 | 0.043 |
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".