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Record W7019547473

From the Graveyard Shift to the Benzene Plume: Visualizing Embodied Work Experience at the Former B.F. Goodrich Tire Factory in Miami, Oklahoma

2023· other· en· W7019547473 on OpenAlexaboutno aff

Bibliographic record

VenueSHAREOK (University of Oklahoma) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsFactory (object-oriented programming)MiamiWork (physics)Embodied cognitionClothingVariety (cybernetics)Competition (biology)Process (computing)
DOInot available

Abstract

fetched live from OpenAlex

From the time of its construction in 1944, to its eventual closure on February 28, 1986, the B.F. Goodrich Tire Factory in Miami, Oklahoma has played an important role in the community. During its 40-year lifetime, it was one of the largest employers in the Ottawa County and Tri-State region (Oklahoma, Kansas, and Missouri), employing over 2,000 workers at its peak. As one community member has noted, “when people got a job at B.F. Goodrich, they thought they had a job for life.” However, this was not to be. On August 23, 1985, a company executive announced that the plant would close in six months, citing increasing competition from foreign producers. In the years following the closure, the site switched owners numerous times while becoming dilapidated. There are also concerns surrounding the use of various chemicals in the production process and an unclear situation regarding who is responsible for cleanup. As a result, the residents of Miami continue to face the consequences of lasting environmental degradation and health concerns.
\n As part of my MS thesis project, I am undertaking multi-faceted mixed-method analysis that seeks to answer the question: how can a Miami community-based organization’s archival materials be incorporated into a StoryMap to engage a community, illustrate the embodied work experience, and introduce the environmental impacts of the five key areas of concern stemming from the plant closure? 
\n Through the use of a variety of quantitative and qualitative data and methods, this research showcases the stories of those who lived, worked, and interacted with the B.F. Goodrich Tire Factory (in the following referred to as “the plant"), where five key items contribute to environmental contamination concerns: Benzene, Asbestos, Carbon Black, Underground Storage Tanks (USTs), and a Solid Waste Disposal Site. To examine these materials and their impacts, I (and others) have conducted a series of interviews with community members about their experiences with environmental contamination and the slow violence resulting from lengthy clean-up endeavors, as well as important areas within the factory site. Additionally, I have organized and analyzed a series of related documents (primarily court proceedings, images, and corporate correspondence) and interviews. I used this qualitative data combined with point locations derived from on-site photographs, to create a community-based B.F. Goodrich ArcGIS Story Map that visualizes work experience at the plant and highlights the environmental and societal impacts stemming from the closure. 
\n After conducting this analysis, I found that: 1. Contamination is a very slow process and slow remediation and observation efforts are needed to address this. 2. Deindustrialization in the United States creates lingering negative societal and environmental impacts. 3. Participatory research (including archival and interviews) that centers the voices of residents via the creation of a StoryMap is a promising strategy for visualizing the events of the Miami plant. 
\n By highlighting community stories, we gain a better understanding of deindustrialization and its connections to places such as Miami across the United States.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0050.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.009

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 head0.037
GPT teacher head0.263
Teacher spread0.226 · 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
Published2023
Admission routes1
Has abstractyes

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