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Record W7001419761

Kathy Oberst Ledger interview, 10 July 2017

2017· article· en· W7001419761 on OpenAlexaboutno aff

Bibliographic record

VenueEngagedScholarship @ Cleveland State University (Cleveland State University) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicNight-time city culture
Canadian institutionsnot available
Fundersnot available
KeywordsLedgerWhite (mutation)PopulationClosure (psychology)Settlement (finance)Quarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

Kathy Oberst Ledger was born in New York and moved as a child to the Detroit Shoreway neighborhood. Ledger recalls when Detroit Shoreway. After getting married she moved to the Clark-Fulton neighborhood, which she recalls had a large Appalachian population mostly from West Virginia. She recalls that many Spanish-speaking residents moved to Clark-Fulton from Tremont. She discusses taking over Judy's White Oaks, a bar her parents ran, and turning it into a nightclub called Diamond Dill's Tropical Lounge in the late 1980s. She contrasts its cosmopolitan clientele from its predecessor's mostly Appalachian white patronage and believes that neighbors' hostility toward this diversity led to the city forcing the club's closure and demolition just two years later after she refused to install a steel beam that an inspector claimed was needed. Ledger has been actively trying to revitalize her community through her own initiatives, working closely with Metro West Community Development Organization, and applying for grants from Neighborhood Connections. Most of her efforts have been geared toward community gardening and positioning the neighborhood as an "International Village."

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0130.001
Scholarly communication0.0010.004
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.066
GPT teacher head0.274
Teacher spread0.207 · 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; both teacher heads agree on what is shown here.

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
Published2017
Admission routes1
Has abstractyes

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