Challenging Exoticization: Maritime Archaeology Logistics in West Africa and East Canada
Bibliographic record
Abstract
Maritime archaeology often leads researchers to far-flung locations. Africa is often acknowledged in Western academic spheres as a challenging archaeological fieldwork destination due to logistical issues like minimal internet resources, language barriers, and unfamiliar legal and physical landscapes. However, these traits are by no means exclusive to the African continent, and perceived difficulty is not a reason to ignore the vast potential of maritime archaeology in Africa. This article explores archaeological practice in two seemingly different regions: Greenville, Sinoe County, southeastern Liberia, and Gaspé Bay, Québec, eastern Canada. A focused look shows how these two areas are actually not so different. Work in these regions has responded to and worked within environmental and climate constraints, engaged communities of diverse stakeholders, battled internet and data access, adjusted to site destruction and topographical change, and worked within funding constraints to pursue new and exciting avenues of study that otherwise would not happen. Ultimately, the conditions of a maritime city or town in which research is based are far less reflective of a country’s wealth and resources than they are of local resources and practice, even in today’s globalized world. The comparison of these two projects brings to light the issue that most maritime archaeologists face: logistically, maritime archaeology can be challenging regardless of a country’s status on somewhat problematic global development indices. Thus, the long-cited issue of “logistics” for dismissing attempts to study African maritime archaeology is unfounded. By emphasizing the commonalities in the constraints and opportunities of our archaeological efforts, we seek to underline the universality of these challenges and our responses to them.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".