Sampled to Death? The Rise and Fall of Probability Sampling in Archaeology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
After a heyday in the 1970s and 1980s, probability sampling became much less visible in archaeological literature as it came under assault from the post-processual critique and the widespread adoption of “full-coverage survey.” After 1990, published discussion of probability sampling rarely strayed from sample-size issues in analyses of artifacts along with plant and animal remains, and most textbooks and archaeological training limited sampling to regional survey and did little to equip new generations of archaeologists with this critical aspect of research design. A review of the last 20 years of archaeological literature indicates a need for deeper and broader archaeological training in sampling; more precise usage of terms such as “sample”; use of randomization as a control in experimental design; and more attention to cluster sampling, stratified sampling, and nonspatial sampling in both training and research.
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.
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 it