Prehistoric Settlement Patterns on the Central Coast of British Columbia
Bibliographic record
Abstract
Over the past half century, archaeologists have been interested in how the environmental variation of the Central Coast has affected settlement patterns. Archaeologists relied on ethnography and subsistence models to explain settlement distribution but were unable to analytically demonstrate influencing factors. The objectives of this thesis were to investigate: (1) the spatial arrangement of sites to examine the types of locations people utilized; and (2) test if the occupational history of a site is reflected by its geographic locations. In this project, site dimension was used as a relative indicator of settlement occupational intensity, and over twenty environmental attributes were tested. Analysis was systematically conducted at multiple spatial scales using GIS. In the first stage the location of shell middens (n=351) were compared against an environmental baseline, derived from a sample of random points. For the second stage, small and large shell middens were compared to test if their locations significantly differed. It was found that shell middens do show an association with certain environmental settings. For some attributes, there was an observable difference in the location of large and small shell middens. However, immense variability was identified and the environmental context of sites greatly determined whether locational preferences could be empirically demonstrated. Overall, large middens, more so than small middens, are located in areas with higher resource diversity. These conclusions support other studies that indicate the relevance of multiple determinants and emphasizes the local nuances of settlement patterning affected by environmental and cultural factors. My results oppose the simplistic and static notion about a prehistoric annual cycle of sedentary winter villages and seasonal resource-specific camps. Improvements to an understanding of settlement distribution can aid in contextualizing specific sites within their regional setting and contribute to our knowledge regarding larger cultural practices such as subsistence and land use practices.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".