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Record W3024180388 · doi:10.1017/s1380203820000094

Life on the fence line. Early 20th-century life in Ross Acreage

2020· article· en· W3024180388 on OpenAlexaffabout
Haeden Stewart, Kendra Jungkind, Robert J. Losey

Bibliographic record

VenueArchaeological Dialogues · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBustFence (mathematics)BoomArchaeologyHistoryExcavationTerm (time)EngineeringEnvironmental engineering

Abstract

fetched live from OpenAlex

Abstract Despite widespread attention to the recent past as an archaeological topic, few archaeologists have attended to the particular social and ecological stakes of one of the most defining material features of contemporary life: the long-term effects of toxic industrial waste. Identifying the present era as the high Capitalocene, this article highlights the contemporary as a period caught between the boom-and-bust cycles of capitalist production and the persistence of industrial waste. Drawing on an archaeological case study from Edmonton, Alberta, we outline how the working-class shanty town community of Ross Acreage (occupied 1900–1950) was formed in relation to the industrial waste that suffused its landscape. Drawing on data from both archaeological excavation and environmental testing, this article argues that the community of Ross Acreage was defined materially by its long-term relationship with industrial waste, what we term a ‘fence-line community’.

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)0.000
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 score0.705
Threshold uncertainty score0.587

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.008
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.105
GPT teacher head0.287
Teacher spread0.182 · 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

Citations8
Published2020
Admission routes2
Has abstractyes

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