Coring, profiling, and trenching: Archaeological field strategies for investigating the Pleistocene-Holocene-Anthropocene continuum
Bibliographic record
Abstract
Archaeologists have long emphasized the importance of large-scale excavations and multi-year or even decades-long projects at a single site or site complex. Here, we highlight archaeological field strategies, termed coring, profiling, and trenching (CPT), that rely on relatively small-scale excavations or the collection of new samples from intact deposits in previously excavated trenches (aka test units or pits). Examples from multiple sites in Africa, Asia, and North America demonstrate that CPT is highly effective for obtaining high-resolution archaeobiological and geoarchaeological samples (e.g., faunal and botanical remains, sediments) and artefacts from areas that have seen limited or no archaeological research, little systematic application of archaeological science methods, or research only on a relatively narrow time period or geographic scale. Designed to complement large-scale excavations at single sites, CPT is ideal for multi-scalar research that works in tandem with remote sensing techniques, providing samples for detailed laboratory analyses and offering a bridge between surface surveys and large-scale excavation. Given the threats facing archaeological sites around the world from climate change and human development, as well as financial, training and infrastructure constraints, and concerns from many Indigenous communities about large excavations, we argue that CPT is an important method for addressing 21st century human-environmental research questions.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".