An Introduction to a Tandem Review on Gayle Fritz’s Feeding Cahokia: Early Agriculture in the North American Heartland
Bibliographic record
Abstract
A tandem review includes two reviewers writing from different angles, with the aim of broadening the scope while building interest in a volume.For example, one reviewer might come from a methodological specialty but not a regional or community-based perspective; adding such a voice brings the reader a broader understanding of the contributions made by the author(s) of a work.Reviewers can request this specifically through email or in a note to the editor while submitting via OJS; alternatively, I may reach out to reviewers with this option.Ethnobiology Letters is pleased to bring readers our first tandem review in volume 15 of Gayle Fritz's Feeding Cahokia: Early Agriculture in the North American Heartland.Kathleen Forste considers what Fritz offers to undergraduate teaching and learning of early agriculture and archaeobotany.Neal Lopinot shares what makes this volume so valuable to archaeologists and archaeobotanical researchers, from regional specialists to global scholars of the origins of agriculture.Individually, they stand alone as important reviews of Fritz's magnum opus; read together, they show the strength of the evidence and breadth of the insights Fritz brings from decades of research into the Eastern Agricultural Complex.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".