MétaCan
Menu
← Back to cohort
Record W7024072618

Proceedings of Expert Forum on First Nations Social Assistance Reform, September 3, 2019

2019· article· en· W7024072618 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationTreasuryPopulationGovernment (linguistics)Social Security ActSocial WelfareMainstreamPoliticsSocial security
DOInot available

Abstract

fetched live from OpenAlex

Social assistance, whether directed to the mainstream population or to First Nations, is not – according to Forum participants -- a sexy topic. Specifically, with respect to First Nation persons living on reserve in Canada, it has been largely a neglected field except for those directly responsible for administering it. Despite its substantive importance, it has not received a lot of attention from the academic research community, for example, nor is it usually near the top of the list of priorities for political leaders and governments.\nWhy is this the case? Perhaps it has to do with the history of providing assistance, which for colonial and federal governments has been seen through the lens of limiting government expenditures. Indeed, the major historical study of this social policy area has the title Enough to Keep Them Alive: Indian Welfare in Canada 1873-1965.1 It may also have to do with the stigma associated with being on welfare, the legacy of the English Poor Laws and their division of the population in need between the deserving and the undeserving poor.\nAs Naiomi Metallic points out in her presentation reproduced below, providing social assistance on reserve also does not rest on a very firm legal foundation. It was in 1964 that federal officials were first given formal authority to allocate funds for assistance, but this was only through a Treasury Board Directive, not through legislation backed by Parliamentary approval. In addition, social assistance is normally provided to Canadian citizens by the provinces, and indeed federal officials in the 1960’s were busy trying to get the provinces on board to deliver assistance on reserve. They were unsuccessful in all cases except Ontario, with the result that “social” has been funded by the federal Indian Affairs department with delivery devolved to individual First Nations. The 1964 Treasury Board Directive tied social assistance to the policies and practices of the provinces and thus did not develop the legal, policy and administrative infrastructure that would normally attend such an important social policy. The provinces, for their part, were understandably focused on the needs of their provincial populations and paid little heed to the implications of their policies and programs for on-reserve populations nor did they consult them when changes were in the offing. Indeed, First Nations have had virtually no input on the matter of social assistance at either the federal or provincial levels.\nYet this social policy area is so important on reserve. As data presented in Andrew Sharpe’s presentation reveal, looking at First Nations across Canada, some 30 per cent of the population living on reserve receives social assistance according to the latest statistics available (2016-17), a number that is six times that for the mainstream population. While dependence rates vary widely from one First Nation to another, almost 40 per cent of First Nations fall into the category of having more than 37 per cent of the population on assistance2. Data reported below indicates that levels of poverty and dependency have declined substantially over the past several decades in the mainstream population, but among First Nation persons living on reserve, poverty and social assistance rates are multiple times higher than they are for the mainstream population.

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)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.969
Threshold uncertainty score0.333

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0060.003
Open science0.0020.004
Research integrity0.0140.007
Insufficient payload (model declined to judge)0.1000.020

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 head0.012
GPT teacher head0.285
Teacher spread0.273 · 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 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueeYLS (Yale Law School)→Same topicIndigenous Health, Education, and Rights→French-language works237,207→