Inter-household transfers of material goods among Sama “sea nomads” of the Philippines: Reciprocity, helping, signaling, or something else?
Bibliographic record
Abstract
The extent to which humans share with both kin and non-kin is a defining characteristic of our species. Evolutionary research suggests that pervasive reliance on inter-individual transfers of goods and services may have evolved to support a cooperative breeding adaptation in humans. However, while intensive food sharing between individuals and families has frequently been investigated in small-scale human societies, a comprehensive analysis of the daily transfers of all material goods has not been attempted. Likewise, while much previous research on cooperative transfers focused on terrestrial foraging populations, less attention is paid to other small-scale economic modalities traditionally inhabited by humans. Drawing on over three years' worth of interviews and observational data from a community of primarily ethnic Sama people residing along the coast of Southern Mindanao Island in the Philippines, this paper examines the overall transfer patterns of material goods in a marine foraging economy. A quantitative description of resource acquisition is followed by an in-depth exploration of the characteristics of individual households and household dyads who gave and/or received more during the study period. Results indicate that a household's age and income are consistently correlated with increased inflow and outflow of material goods. Results also suggest differential motivations underlie inter-household sharing of food, money, and other goods in the study community. Most importantly, we find that both daily and long-term reciprocity overwhelmingly drive sharing within household dyads in the study community, despite secondary effects of kinship, relative need, and relative household age between household dyads.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".