Arctic visible: Mapping the visual representations of indigenous peoples in the nineteenth-century western arctic
Bibliographic record
Abstract
This paper describes progress of the ongoing postdoctoral project ARCVIS. The project is funded by a two-year individual fellowship from Marie Skłodowska-Curie actions (2019-2021). ARCVIS gathers, maps, and disseminates representations of Indigenous peoples in the western Arctic (Greenland, Canada, Alaska) between 1800 and 1880. The material is comprised of watercolours, pencil sketches, photographs, and prints, such as lithographs, woodcuts, and engravings. The visual material is scattered in archives around the world and this project's aim is to gather that material together and display it geographically, linked to its places of origin in the Arctic. A key element of this project is the collation and interpretation of the material through an open access online geospatial platform, which combines the visuality of exploration and travel with digital methods that seek to bring out the richly contextual information often bypassed in visual documentary records. The project will present the peopled western Arctic that was encountered by 'explorers.' Through the analysis of picture and text in archives and published nineteenth-century texts, it will strive to give 'voice' to the Indigenous people who were key to the success or failure of expeditions from the south. The project challenges the common outsider perception of the Arctic, which is often seen as an empty, icy region, devoid of human populations. Due to the COVID-19 pandemic, it has not been possible to include 'new' archival sources and the online platform will now only use images and texts available online and in the public domain.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".