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Record W6959893939 · doi:10.11575/prism/32678

An Evaluation of Alberta's Family Law Act

2009· other· en· W6959893939 on OpenAlexaboutno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2009
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationFamily lawStatutory lawWorkloadSubstantive lawOrder (exchange)Common lawProcedural lawPublic law

Abstract

fetched live from OpenAlex

The Alberta Family Law Act (FLA) was enacted on October 1, 2005 in an effort to modernize, rationalize and consolidate Alberta family law, streamline court procedures, and provide a non-adversarial approach to resolving family conflict in the best interests of children and families. With funding form the Alberta Law Foundation, the Canadian Research Institute for Law and the Family (CRILF) conducted a two-year evaluation of the legislation in order to determine whether the procedural and substantive changes are fair, effective, and efficient. The objectives of this study were to: 1. Develop a detailed evaluation framework, including measurement tools and instruments. CRILF worked with the Steering Committee to determine what was feasible in terms of data collection and measurement. The evaluation framework guided the remainder of the project; 2. Evaluate the impact of the procedural changes that have resulted from the FLA. A significant change under the Family Law Act was the streamlining of court procedures. The project examined the impact of this change on workload to see if the Act has been successful in its objectives of procedural effectiveness, efficiency, and accessibility; 3. Evaluate the impact of the substantive changes outlined in the FLA. Substantively, the Family Law Act deals with all aspects of family law in a nondivorce context. The Act recognizes changing social conditions and updates key legal concepts. It is important to assess whether the changes have been fair, effective, and efficient; and, 4. Inform recommendations to improve the effectiveness of the FLA and to fine tune provisions.

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)0.079
metaresearch head score (Gemma)0.116
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: Other
Teacher disagreement score0.150
Threshold uncertainty score0.986

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0790.116
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.007
Science and technology studies0.0080.005
Scholarly communication0.0080.002
Open science0.0040.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.019
GPT teacher head0.212
Teacher spread0.193 · 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
Published2009
Admission routes1
Has abstractyes

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