Bibliographic record
Abstract
In this article I compare the story of the first contact tribute giraffe sent from Bengal to China in 1414 with the story of April, the famously web-cam pregnant giraffe of 2017. Both giraffes were transported by new technologies that brought together geographically dispersed people through a notable event. Both giraffes had to be conveyed from natural habitats into confinement, from distance into quasi-intimacy with European and global observers, from matriarchal family structure into an individual with a face that could at least hypothetically look back at its human viewer. The space between these two events has been marked by the emergence of a capitalist world order together with growing public anxiety about environmental risk. This shared precarity, commonly named the Anthropocene, is widely conceptualized as the result of human domination of and estrangement from nature. But the history of the giraffe reminds us that some people were estranged from nature, while others were defined by and exploited precisely because of their proximity to its resources. Each step of being made visible has relied on something else being made invisible. The double act of foregrounding and disappearing has discursively shaped both our relations with animals and the visual aesthetics of modern culture. To borrow Marshall McLuhan’s well-known phrase, the medium is the message, and in this article, the medium is an animal. Two giraffes, two historical eras, two distinct sociopolitical and technological situations. Why giraffes, and what are they mediating?
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.019 | 0.013 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.027 | 0.004 |
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".