Hippocampus Cognitive Map: Enacting Cosmologic Scene Imagery of Human Origins from Haida Gwaii within an Experimental Digressive Assemblage
Bibliographic record
Abstract
The ability to be affected by the Northern Raven's vital materiality in the Yukon Boreal Forest of Canada prompted my creative desire to explore a novel digressive approach to the plot of human origins, specifically from the Cascadia Subduction Zone (CSZ). This tectonic plate boundary extends from Northern Vancouver Island to Cape Mendocino, California. As part of the Pacific Ring of Fire, the CSZ has experienced significant geological activity, which is evident in recent archeological records showing that villages along the coast were abandoned and submerged approximately 3,000 years ago during the late Holocene due to earthquakes and tsunamis. To challenge our perception of cosmological myths, I focus on two ancient stories from the oral tradition of Haida Gwaii (formerly known as the Queen Charlotte Islands), as recorded by John Reed Swanton: "Raven discovered many people inside a cockle" (Boas and Swanton 1905b, 320), and "Sing 7agang qiidaraagan - How Shining-Heavens caused himself to be born" (Swanton 1905b, 26). From a cognitive evolutionary perspective, two visual scenes highlight these stories: (1) the ocean-to-land transition of protohumans, as observed in the intertidal zone at Rose Point (Nai-koon) and Kaisun, and (2) the niche construction by organisms and the co-evolution of their ecological roles. Given the significance of oral tradition in a specific ecological niche on Earth, I hypothesize that sequentially ordered narrative events are interwoven within a hippocampal cognitive map, which supports long-term episodic memory. To explore this cognitive map, I will correlate visual scene imagery with recent studies on the emergence of cellular life (approximately 4.2 billion years ago), the development of cellular sentience and cognition, the niche construction by organisms, the neural substrates involved in encoding long-term episodic memory, and the crucial role of the hippocampus in imagination and cognition.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".