Bibliographic record
Abstract
Banking is going mobile and becoming social. Today your smartphone is your own personal and portable bank vault, allowing you to access, deposit and transfer money with a light caress of your screen and a deliberate tap on an imaginary digital button. Our devices, in other words, are allowing money and debt to achieve what money has always ‘desired’ – ubiquity, immateriality, infinite accessibility and instantaneity. Moreover, connecting banks with customers’ mobile devices using proprietary apps allows the relationship between banks and their creditors and debtors to become deeper, more profound, more granular. This granularity, of course, is primarily a one-way street defined more by the banks' access to user-generated content, purchasing patterns and their geo-spatial and temporal coordinates than by customers' desires, priorities or demands. Through the power of mobile devices, then, the pre-existing asymmetries related to knowledge, access to information, transparency and surveillance between banks and their customers are further extended in the bank’s favour. That is, by providing customers with the appearance of access and interactivity, app-based banking allows the financial system to extend its ability to track, surveil, judge, influence and control credit-seeking populations in ever more precise and predatory ways. In this paper I suggest that the extension of banking services onto our smartphones is not so much a convenience or service as it is the manufacturing of yet another market – a mobile banking market – that enables the banking system to track and tag the trajectories of the spaces in between more conventional points of exchange. I suggest also that mobile banking apps serve to whet the appetite of consumers for a cashless future of digital currencies which economists argue is necessary – or even inevitable – in the face of what economists call the ‘zero lower bound’ – the financial quandary that results when interests rates hit 0 percent and financial stimulus using lower interest rates becomes impossible in a world where cash remains an option.
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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.016 | 0.021 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".