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Record W4380739751 · doi:10.3138/uhr-2022-0021

Inventories, Interiors, and Women’s Ambitions: Strategies of Property Ownership in Three Mid-19th Century Montreal Public Houses

2023· article· en· W4380739751 on OpenAlexaffvenueabout
Mary Anne Poutanen

Bibliographic record

VenueUrban History Review · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsArgument (complex analysis)Capital (architecture)Property (philosophy)BusinessComposition (language)Set (abstract data type)Public propertySociologyPublic relationsMarketingLawLaw and economicsProperty rightsPolitical scienceHistory

Abstract

fetched live from OpenAlex

Notarized inventories provide an important window onto the interiors of public houses, the image that keepers sought to project of their businesses and of themselves, and the type of guests they wanted to attract. In this micro history, I examine the degree of differentiation amongst three widows operating modest businesses located in highly trafficked Montreal neighbourhoods, in particular, the composition of their domestic capital, the business strategies they employed, and if they achieved social mobility. We know from earlier studies that movables were significant assets for earning a living, often critical to the survival of a widowed, separated, or abandoned woman. My argument goes further. I contend that women attempted, and some were able, to convert movables into immovable property, assets that were more secure and versatile. While publicans displayed a wide array of skills, statuses, and achievements, these three cases focus on the critical threshold, that interesting set of people at the boundary, aware of and struggling to achieve property ownership.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.330

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.009
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.103
GPT teacher head0.225
Teacher spread0.122 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2023
Admission routes3
Has abstractyes

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