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Record W7115713601 · doi:10.4324/9781003635550-13

Not in My Back Yard, Not My Problem

2025· book-chapter· en· W7115713601 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsnot available
Fundersnot available
KeywordsSilencePower (physics)PhenomenonSocial issuesMental healthNatural (archaeology)

Abstract

fetched live from OpenAlex

One need not look to the Global South or conflict zones worldwide to find marginalized and oppressed communities. Canada has one of the highest living standards in the world. Yet, many of our citizens live unhoused or with unstable power, undrinkable water, and insecure food supply. In the larger urban centres people seem to have become accustomed to stepping over unhoused people who are dying in the streets, or they avoid visiting the impoverished core neighbourhoods altogether. Countless individuals suffer from mental health challenges or addictions exacerbated by poverty. Most will not act unless they cannot avoid what is occurring in their own backyard. Society would rather hide the undesirable lifestyles and way of life of the homeless, poverty-stricken, criminal, or addicted individuals by congregating them in impoverished neighbourhoods. Many feel that if these social blisters are out of site, and “not in my back yard” (NIMBY) then they are someone else’s problem. We should all feel responsible to overcome this culture of indifference and silence as NIMBYism has a high societal cost to everyone, especially in the city of Winnipeg and other Canadian cities. This chapter explores the phenomenon of inaction, denial, and how the average person is called to act on social issues in their communities. We examine the power of adding to the discourse around social responsibility to raise awareness and inspire people to make positive contributions in their communities.

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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.942
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.034
GPT teacher head0.302
Teacher spread0.268 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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