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Record W357382677 · doi:10.51644/mtzq8759

The Balance of Fairness in Family Relations: A Contextual Family Therapy Case Study

2014· article· en· W357382677 on OpenAlexaff
D. Bruce MacLeod, Agus Sadewa, Ruth Ann Arthur, Kelly Collins, Tracey Hand-Breckenridge, Yvonne Runstedler, Kellie Van Hooren

Bibliographic record

VenueConsensus · 2014
Typearticle
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsBalance (ability)Family therapyPsychologySocial psychologySociologyPsychotherapist

Abstract

fetched live from OpenAlex

Case Scenario:Mary is not sure anymore if she has a problem or is the problem.Family life had never been free of the stresses that come with raising two children and managing a household with her husband who is on the road five days of the week but all in all she feels that she is managing, even happy with her life and the home she has created for her family.That was, until the morning that John Jr. tells her he hates her.For months John Jr. had been surly.Where was the fun loving child who would bolt out the door the second he heard Dad's truck tires crunch on the gravel driveway, madly pulling his arm up and down until his Dad honked that truck horn?Now he locks himself in his room, is absent from family meals and missing school.With her other son Phillip away for his first year of university -the house feels very lonely.When she later found the missing grocery money in the pocket of John Jr.'s jeans, her concern and loneliness deepened.His father, John Sr., had confronted him days before and escalated the entire situation by yelling at him to smarten up or get the heck out of the house.With her school and work duties, she is often busy but she set aside some time to have a heart to heart at the breakfast table with John Jr. hoping he might share what is happening.It did not go as she planned and her anxiety made her questions sound more like an interrogation that ended abruptly with John Jr. yelling at her: "You do not have a clue what was really going on in my life and to get out of my life."She tried to hold him but he pushed her away and stormed out the door.Crying, she picked up the phone and called her friend the pastor for help not sure anymore if it is her husband, child or herself who need help the most.

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)0.000
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 score0.260
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.037
GPT teacher head0.321
Teacher spread0.284 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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