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Record W4283735790 · doi:10.25071/2292-6739.130

Upsetting Constructions of Safety

2022· article· en· W4283735790 on OpenAlexaffvenue
Sydney Chapados

Bibliographic record

VenueContingent Horizons The York University Student Journal of Anthropology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPovertyAutoethnographySociologyFace (sociological concept)Construct (python library)Class (philosophy)Political economyCriminologyGender studiesAestheticsPolitical scienceLawEpistemologySocial science

Abstract

fetched live from OpenAlex

This article examines how certain neighbourhoods and the populations that reside in them might be understood as safe and good by presenting observations from a walking, autoethnography through and around the suburb in which the author resides. The messages that societies receive and internalize about people who experience poverty are primarily constructed out of neoliberal institutions that uphold the idea that those who live in poverty are there by choice or incapacity and face the appropriate consequences of that choice. Neoliberal discourses devalue the lives of those experiencing poverty by suggesting that they are morally, physically, or mentally incapable of being responsible for themselves. While anyone could potentially experience poverty, the relational construct of the upper class/lower class creates a metaphorical divide that requires deep rethinking to transcend. When spaces are demarcated as unsafe or violent, other spaces are relationally marked as safe or secure. The article concludes that controlling outward appearances largely creates and reinforces constructions of suburban areas as safe in relation to the construction of other areas as unsafe and violent. However, the intensive focus on controlling appearances leads to a mistrust of others and the sacrificing of communities that once existed and thrived.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.361
Teacher spread0.331 · 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 teacher head, not a consensus.

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

Citations1
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueContingent Horizons The York University Student Journal of AnthropologySame topicHomelessness and Social IssuesFrench-language works237,207