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Record W2175821059

Father Involvement Research Alliance (FIRA): Reporting in a CURA Partnership

2011· article· en· W2175821059 on OpenAlexfundaboutno aff
Anne Bergen, Linda Hawkins, Kerry Daly

Bibliographic record

VenueThe Atrium (University of Guelph) · 2011
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
FundersOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsGeneral partnershipAllianceGovernment (linguistics)Work (physics)Strategic alliancePublic relationsTracking (education)SociologyBusinessPolitical scienceEngineeringPedagogy
DOInot available

Abstract

fetched live from OpenAlex

FIRA is a pan-Canadian alliance dedicated to developing and sharing of knowledge focusing on father involvement. The FIRA community university research program (2003-2009) involved 8 universities and 35 community partners across Canada, directed by Kerry Daly and coordinated by Linda Hawkins at the Centre for Families, Work & Well-Being. Work included collaborating and sharing information with fathers and mothers, academics; social, health and other service providers; educators; employers and the business sector; community, professional and labour groups, government. Tracking a diverse set of products from the work was part of the original design for the project. This poster visually demonstrates what good reporting tools within a partnership can create. It is also important to note that partnership products were tracked as evidence of impacts. www.fira.ca

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)0.106
metaresearch head score (Gemma)0.098
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.106
Threshold uncertainty score0.560

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1060.098
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0090.002
Scholarly communication0.0060.004
Open science0.0020.009
Research integrity0.0010.002
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 head0.307
GPT teacher head0.388
Teacher spread0.081 · 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
Published2011
Admission routes2
Has abstractyes

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