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Record W4234677774 · doi:10.32920/ryerson.14661753.v1

Ethnographic journalism and the American urban crisis

2021· preprint· en· W4234677774 on OpenAlexaff
Juan Miguel Villa

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsToronto Metropolitan UniversityYork University
Fundersnot available
KeywordsEthnographySociologyUnderclassPrejudice (legal term)JournalismEmpathyGentrificationScholarshipMedia studiesEpistemologyPolitical scienceSocial psychologyLawPsychologyAnthropology

Abstract

fetched live from OpenAlex

The historical role of racial prejudice in the development of black ghettos by the I990s has been a source of contention in urban studies. This paper contends that works of ethnographic journalism such as Alex Kotlowitz's There are no Children Here, David Simon and Ed Bums's The Corner, and Leon Dash's Rosa Lee are critical texts for gaining an informed understanding of the urban crisis because they allow one to make connections with both the empirically observable facts and the shared social experience of the black underclass. By revealing the importance of viewing positivist and interpretivist understandings of the American city as complementary rather than oppositional, these works provide a multifaceted, rather than mutually exclusive, framework for understanding the American urban crisis. This approach allows us to avoid the ontological shortcomings present in traditional methodologies for examining urban poverty-shortcomings that take root in discursive tensions regarding the nature of prejudice in municipal development. Ethnographic journalism evokes the empathy necessary to view urban squalor as a practical concern rather than a spectacle.

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)0.009
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.006
Science and technology studies0.0140.032
Scholarly communication0.0120.008
Open science0.0010.007
Research integrity0.0020.002
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 head0.057
GPT teacher head0.277
Teacher spread0.220 · 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 designQualitative
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
Published2021
Admission routes1
Has abstractyes

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