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Record W2315012554 · doi:10.1177/2373379916630993

Reflexivity in Sexual Health Pedagogy

2016· article· en· W2315012554 on OpenAlexaff
Lawrence Nyika, Angellar Manguvo, Fungai Zinyanduko

Bibliographic record

VenuePedagogy in Health Promotion · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Realism in Sociology
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsReflexivitySociologyAgency (philosophy)Sociocultural evolutionIdentity (music)Social constructivismHuman sexualitySocial psychologyGender studiesPsychologyEpistemologyPedagogySocial scienceAesthetics

Abstract

fetched live from OpenAlex

Youth face a daunting task transitioning the ever-changing contemporary world, which often causes them to engage in self-talking. Employing sociological perspectives of critical realism, Margaret Archer used the term reflexivity to describe the process of self-talking and how it mediates between social structure and human agency or the ability to act. This reflexivity or self-talk is exercised in various ways as determined by a person’s concerns, aspirations, and nature of relationships with the social environment. In this article, we examine this perspective of reflexivity and its implications for school-based sex education. We show how reflexivity intersects with the concept of identity to provide important insights into why youth behave differently in similar social situations. Thus, we argue, there is a need to tailor sex education to students’ sexual behavior identities. It is crucial to situate contemporary sexual health pedagogy within social constructivist and critical theory perspectives because sexual behavior identities are influenced by many sociocultural constructs. The article concludes with examples of empowering sex education instructional strategies.

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)0.020
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0050.049
Scholarly communication0.0080.007
Open science0.0010.008
Research integrity0.0040.008
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 head0.195
GPT teacher head0.566
Teacher spread0.371 · 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 designTheoretical or conceptual
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

Citations3
Published2016
Admission routes1
Has abstractyes

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