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Record W2065631333 · doi:10.1177/0170840614550730

The Calculation of Age

2014· article· en· W2065631333 on OpenAlexaffabout
Cameron Graham

Bibliographic record

VenueOrganization Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsYork University
Fundersnot available
KeywordsConstruct (python library)Agency (philosophy)Order (exchange)Capital (architecture)Corporate governanceInvestment (military)PopulationPoliticsEconomicsPopulation ageingSociologyFinancePolitical scienceSocial scienceLaw

Abstract

fetched live from OpenAlex

This article explores the role of calculative technologies, such as taxation, accounting and actuarial practices, in constructing ‘age’ in contemporary society. It argues that retirement income programs built on these technologies attempt to construct specific relations not just between the individual and other generations, but between the individual and herself at other stages of life. Retracing the series of Canadian attempts to secure income for the elderly over the course of the 20th century, the paper shows how calculative technologies have been used to connect responsibility for the elderly to the political rationalities of the day. This genealogy allows us to recognize how the present Canadian retirement income system, with its public and private programs addressing different subsets of the population, is contingent on neoliberal rationalities of governance. These demand the alignment of the individual with the goals of the capital markets, and seek to achieve this through a distributed agency that encourages the investment of individual savings in retirement income products. The paper argues that this distributed agency is perpetually incomplete, and that uncertainty is necessary in order that the individual be constantly remade as an investor.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.272
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.189
GPT teacher head0.432
Teacher spread0.243 · 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 designObservational
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

Citations8
Published2014
Admission routes2
Has abstractyes

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