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Record W4381093512 · doi:10.32920/ifmj.v3i2.1738

Microbial Syntrophy

2023· article· en· W4381093512 on OpenAlexvenueno aff
Jenifer Wightman

Bibliographic record

VenueInteractive Film and Media Journal · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsCurrencyValuation (finance)Value (mathematics)Liberian dollarEconomicsEconomyBusinessMarket economyLaw and economicsCommerce

Abstract

fetched live from OpenAlex

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.008

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.

Opus teacher head0.009
GPT teacher head0.234
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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