Bibliographic record
Abstract
While the gift economy is often considered a mechanism to strengthen social ties, the grift economy is often considered detrimental. However both systems rely on reciprocal play adding complexity to and questioning the ‘valuation’ mythology in contemporary free market logic. While traditional markets rely on so-called mutually agreed upon standards or market levers (value of currency, democratically decided upon regulations, legal precedents for civil behavior, global agreements for free exchange, supply-demand curves driving price), it is clear that this system has many games, loopholes, subsidies, institutional baggage, infrastructural lineages, national perversions, and theoretical distortions that make this free market, not actually free to correct its perversions on contemporary ‘value’ or inherited wealth inequity based on historic values. Gifters and grifters both contest value and do so by engaging existing social systems in unconventional ways. They work together, differently. In this presentation, I will playfully explore various theories about microbial economies that share gift/grift-like economies that support diverse bodies of life within a finite ecosystem of natural resources. For example, imagine a humanly visible maize root compared to an invisible microorganism; the single-celled bacteria cannot simply chew up the root that is orders of magnitude larger than itself (most microbes have a diameter between 0.5-10 microns, roughly the same range in size of ground corn starch). The scale of the opportunity for a microbe to eat a complex foodstuff like maize is Herculean! One form of microbial collaboration is called syntrophy. In this example, microbes living in environments without oxygen participate in an enzymatic potlatch. Different species contribute different enzymes to the extracellular matrix (outside the microbe body where the large molecule resides). Collectively these different donated enzymes with different capacities incrementally breakdown the complex substrate (the food). When the food is broken down into small enough metabolites, these basic building blocks of life in the extracellular matrix are now small enough to be absorbed by the small microbes (not unlike what happens in our stomachs) for maintenance, growth, or reproduction. Microbes share their genetic resources (in the form of donated enzymes) to then be able to collectively harvest the resulting metabolites in the commons of their extracellular space. In this case, it literally takes a village to make the village; losing certain species (and associated enzymes in the shared metabolic supply chain), breaks the collective system of metabolism to access the building blocks of the maize root. Just as in gift, grift, and current capitalist markets, the microbes deploy different agents to play different roles to access and distribute resources necessary for life. What is missing from this microbial system (in my anthropocentric read) is a perverse consent to value oneself and others’ worth, independent of the material needs of all. This talk will share observations from my art practice of transforming microbial ecosystems, present synopses of various theories on microbial ‘economies’, and then reflect back on two fringe human economies (gift/grift) to re-consider how we might build equitable and just collaborations to live sustainably within our own finite world.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.008 |
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".