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"A search for understanding: A proposal for researching Native homelessness in Northern Manitoba"

2003· article· en· W6244188 on OpenAlexaboutno aff
Greg Fidler, Colin Bonneycastle

Bibliographic record

VenueFEBS Letters · 2003
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyGeographyPolitical science

Abstract

fetched live from OpenAlex

Poverty has been a prevalent issue throughout world history.
\nDespite the United Nation's opinion that we have the best quality of life, Canada cannot say that 
\n it is the exception to this rule. Many people live in abject poverty here. Without an 
\nofficial poverty line to help determine the level of poverty, estimating the actual number of poor 
\nis a contentious issue. Most official reports base their findings on Statistics Canada's Low 
\nIncome Cut Offs (LICO's). For example, the National Council of Welfare estimate that in 1997 just 
\nover five million Canadians, or 17.2% of the population, were living in poverty (Silver,2000). 
\nSuch findings generally underestimate the number of poor Canadians as they usually do not 
\ninclude data on Aboriginal people living on reserves, residents of the Yukon, Nunavut, 
\nand North West Territories, and people who live in institutions. The costs surrounding 
\npoverty are enormous. For example, population health studies show a strong correlation between 
\npoverty and people's health. They argue that poverty contributes to many of our social ills, 
\naffecting individuals, families, communities and society as a whole (for example, see Layton, 
\n2000). Though there are discrepancies in the actual rates and effects of poverty, poverty rate and 
\npopulation health studies have one major commonality, they indicate that poverty is increasing 
\n(Ross, Scott, & Smith,
\n2000). At the margins of this growing trend, one often finds the homeless.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.782
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.150
GPT teacher head0.430
Teacher spread0.280 · 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.

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
Published2003
Admission routes1
Has abstractyes

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