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Record W7290167

WFCR interviews Psychological Services Center Director Christopher Overtree about support groups for military families

2007· article· en· W7290167 on OpenAlexaboutno aff
Christopher E Overtree

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsCenter (category theory)PsychologyManagementSocial psychologyApplied psychologyPublic relationsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Western Massachusetts military families will get help from two new support groups being offered by UMass Amherst's Psychological Services Center. Dr. Christopher Overtree, the PSC's Director, says the aim of the support groups is to help family members maintain a healthy relationship with their loved one in Iraq or Afghanistan, while meeting the daily demands of everyday life at home. Overtree says multiple tours of duty in Iraq and Afghanistan, and extended deployments are taking their toll on the mental health of relatives. one of the groups will be for the parents and spouses of those that are on active duty abroad. The other will be specifically for the children of those in the military, and will use arts, crafts and games to help kids explore their concerns about their parents. both groups will begin meeting in November. Overtree says multiple tours of duty in Iraq and Afghanistan, and extended deployments are taking their toll on the mental health of relatives. One of the groups will be for the parents and spouses of those that are on active duty abroad. The other will be specifically for the children of those in the military, and will use arts, crafts and games to help kids explore their concerns about their parents. Both groups will begin meeting in November.

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)0.003
metaresearch head score (Gemma)0.013
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0230.002

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 head0.033
GPT teacher head0.365
Teacher spread0.333 · 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
Published2007
Admission routes1
Has abstractyes

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