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Record W2070268374 · doi:10.1177/0020872807081899

Social and economic justice, human rights and peace

2007· article· fr· W2070268374 on OpenAlexaffabout
Colleen Lundy, Katherine van Wormer

Bibliographic record

VenueInternational Social Work · 2007
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Policies
Canadian institutionsCarleton University
Fundersnot available
KeywordsHumanitiesMilitarizationPolitical scienceSocial justiceHuman rightsSociologyPolitical economyLawPhilosophy

Abstract

fetched live from OpenAlex

English Social work in Canada and the USA shares a common heritage in the commitment to advancing social and economic justice. Today the capitalist global market and increasing militarization affect social work in both nations. This paper discusses these challenges and presents a vision for social work as a human rights profession. French Au Canada et aux É tats-Unis, le travail social partage l’héritage d’un engagement à faire évoluer la justice sociale et économique. Aujourd’hui, la mondialisation du marché capitaliste et la militarisation croissante ont un impact sur le travail social dans les deux pays. Cette étude se penche sur ces enjeux et formule une vision du travail social en le considérant comme une profession liée aux droits de la personne. Spanish El trabajo social en Canadá y los Estados Unidos comparte una herencia común en su compromiso de avanzar hacia la justicia social y económica. Actualmente, el mercado global capitalista y la creciente militarización impacta al trabajo social en ambas naciones. Este trabajo discute estos retos y presenta una visión para el trabajo social como profesión de los derechos humanos.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.893
Threshold uncertainty score0.284

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0260.030
Scholarly communication0.0080.003
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.039
GPT teacher head0.388
Teacher spread0.349 · 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 designTheoretical or conceptual
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

Citations48
Published2007
Admission routes2
Has abstractyes

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