Bibliographic record
Abstract
Due to the unrivaled efficiency of digital banking, paper currency is facing obsolescence.Profiles may be permanently etched on the surface of bank notes, coins, and cheques, but the manner in which these vestiges narrate our lapsed human relationships will ultimately contribute to re-defining a nation's identity, and the space of its capital city.Over the past quarter century, Caracas, Venezuela has been subject to a spectrum of economic trends: politically advantageous oil trades in the 1980s and 1990s, The 1994 Banking Crisis, inflation rates reaching an annual height of 500% from 2015 to 2017, and a series of corrupt administrations which have ignited heinous crimes, ongoing exponential growth in impoverished neighbourhoods, and the current extreme shortages of basic living supplies.It has been labeled the world's most violent city.This thesis will investigate the capital city of Caracas and its systems of exchange, expropriations and exploitation, all in the context of an evolving spatial currency.It will ask the question: how can we reveal exchange value as a function of spatial networks, and at shifting scales?Annotation by original author.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".