Bibliographic record
Abstract
Finance is a critical dimension of life for most contemporary human beings. Finance refers to the management of money as debt, credit, or capital. Financial practices and techniques date to the dawn of human communities characterised by the division of labour. Indeed, the earliest written records kept in ancient Mesopotamia are records of credit and debt. As such, finance should not be understood as a synonym for capitalism or modernity, but rather as means of administering populations through the management of money. Financial instruments have been deployed in economic systems based on both markets and redistribution. More recently finance has become increasingly indispensable to the organisation of human life, an essential economic sector, and a key domain of employment. As such, it has attracted the attention of anthropologists seeking to understand the systems and practices that undergird human organisation, production, and motivation. Historically, anthropologists have focused most intensively on personal finance, beginning with rotating credit associations and continuing through development initiatives premised on microfinance. More recently, corporate finance has come into focus, with critical work on the discursive practices of market traders, investment bankers, and financial analysts. Less attention has been paid to public finance, with the notable exception of ethnographic research in central banks and newer work on pension funds and municipal bond markets. Anthropology has played a critical role in understanding the black box that is contemporary finance by addressing its practices and its effects on human beings today.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.314 | 0.163 |
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".