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Record W2229365354 · doi:10.7146/pl.v30i1.8707

2.21 BILLION REASONS: Creating Safe Environments for Children

2009· article· en· W2229365354 on OpenAlexaff
Judi Fairholm, Gurvinder Singh

Bibliographic record

VenuePsyke & Logos · 2009
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Medical Studies
Canadian institutionsCanadian Red Cross Society
Fundersnot available
KeywordsMultitudeContext (archaeology)CriminologyNationalityPolitical scienceSociologyPublic relationsEconomic growthLawGeographyImmigration

Abstract

fetched live from OpenAlex

»NO VIOLENCE AGAINST CHILDREN IS JUSTIFIABLE; ALL VIOLENCE AGAINST CHILDREN IS PREVENTABLE.« Violence touches everyone; it either hides behind the closed doors of homes and institutions, or it permeates every aspect of life through war and conflict. It is a daily reality for millions of people around the world, affecting all ages and both genders within every social context and nationality. Violence is a complex problem related to patterns of individual thought and behaviour that are shaped by a multitude of forces within relationships, families, communities and societies. It is a health, social, justice, legal, economic, spiritual, development, risk management, and human rights issue. Although violence impacts members in every community and society, children and youth are the most vulnerable. In every part of their lives – their homes and families, schools, institutions, workplaces and communities – children are beaten, sexually assaulted, tortured, neglected, maimed, bought and sold, and killed. Far too often the adults in their lives are the perpetrators of their pain or the »observers« and take little or no responsibility to protect them and create safe environments. The consequences are enormous – at the individual, family, community, and societal levels.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.059
GPT teacher head0.429
Teacher spread0.370 · 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 designObservational
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
Published2009
Admission routes1
Has abstractyes

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