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Record W2794311208 · doi:10.1080/10911359.2018.1426071

The social construction of a possible male gender bias is negatively impacting fathers in child welfare services: Hammering a square peg into a round hole

2018· article· en· W2794311208 on OpenAlexaff
Virginia Amato

Bibliographic record

VenueJournal of Human Behavior in the Social Environment · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsWelfareSocial WelfarePsychologySocial workDevelopmental psychologyWelfare systemSocial psychologyGender studiesSociologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

The social construction of gender dictates the masculine and feminine roles deemed appropriate within a society. Society has traditionally socially constructed women to be mothers and the primary parent, leaving fathers much too often on the sidelines of parenthood. For example, if a parent is a man, they have fewer rights than a parent who is a woman. Gender biases in society are insidious problems. Such biases can lead to the development of adverse attitudes, beliefs and unfair treatment of members of these groups by both individuals and social institutions. This paper will demonstrate the need to investigate the possibility of a systemic male gender bias in CWS. The paper will include the statement of the problem, the rationale and the framework of how gender is socially constructed to help in the understanding of how it negatively impacts fathers. Next will be a discussion of avoiding fathers at all six principle phases of CWS, the lack of parent programs specific to fathers, direction for future research and potential research implications for fathers, children and child welfare workers.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
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 head0.055
GPT teacher head0.335
Teacher spread0.280 · 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.

Study designQualitative
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

Citations9
Published2018
Admission routes1
Has abstractyes

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