Bibliographic record
Abstract
If … by observing the adaptive behavior of any living society, we can derive predictions about that society's discards, we are doing living archaeology. ( Richard Gould 1980: 112 ) Household no. 1 collected their domestic refuse, including tin cans, in a large duffel bag which was later transported by canoe to a lake about 19 km from the residential camp. ( Robert Janes 1983: 32 ). We start the chapter by introducing relevant concepts and ideas of middle range theory, especially those concerned with processes relating to the transfer of materials from the systemic to the archaeological context (S–A processes). We then survey their application to deposits and sites and consider the effects of processes such as curation on the archaeological record. A processual and a postprocessual case study relating to residues are presented and critiqued, and the chapter concludes with a consideration of the ethnoarchaeology of abandonment. Middle range theory from S to A Some regard “the reconstruction of prehistoric lifeways in the form of prehistoric ethnographies to be an appropriate goal for archaeology,” while others consider rather “that we should be seeking to understand cultural systems, in terms of organizational properties,” as Binford (1981b: 197) argued in his “Pompeii premise” paper. Many take an intermediate view: To analyze archaeological units without referring back to where they came from and to what they represent is to divest such units of most meaning.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.022 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".