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Record W2122215864 · doi:10.1068/a38287

Technology and the Architecture of Markets: Reconfiguring the Canadian Equity Market

2007· article· en· W2122215864 on OpenAlexaboutno aff
Niall Majury

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsnot available
Fundersnot available
KeywordsSociotechnical systemCorporate governanceEquity (law)Control reconfigurationIndustrial organizationStock exchangeSituatedEconomicsBusinessMarket economyEconomic systemFinanceEngineeringPolitical scienceComputer scienceManagement

Abstract

fetched live from OpenAlex

This paper examines the relation between technical possibilities, liberal logics, and the concrete reconfiguration of markets. It focuses on the enrolling of innovations in communication and information technologies into the markets traditionally dominated by stock exchanges. With the development of capacities to trade on-screen, the power of incumbent market makers has been challenged as a less stable array of competing quasi-public and private marketplaces emerges. Developing a case study of the Toronto Stock Exchange, I argue that narrative emphasis on the performative power of sociotechnical innovations, the deterritorialisation of financial relations, and the erosion of state capacities needs qualification. A case is made for the importance of developing an understanding of: the spaces of encounter between emerging social technologies and property rights, rules of exchange, and structures of governance; and the interplay of orderings of different institutional composition and spatial reach in the reconfiguration of market architectures. Only then can a better grasp be gained of the evolving dynamics between making markets, the regulatory powers of the state, and their delimitations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.190
Teacher spread0.177 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations9
Published2007
Admission routes1
Has abstractyes

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