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Record W4406311945 · doi:10.7202/1115435ar

Between Two Worlds: Promoting Identity Development in Middle School

2023· article· en· W4406311945 on OpenAlexaffabout
Kenneth Lloyd Reimer

Bibliographic record

VenueInternational Journal for Talent Development and Creativity · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicJewish Identity and Society
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsIdentity (music)Development (topology)SociologyAestheticsArtMathematics

Abstract

fetched live from OpenAlex

This paper highlights a (2022) study conducted in a Canadian school division with middle school teachers. The purpose of this study was to learn what middle school teachers did to positively connect with their students. Due to COVID-related concerns, four participants were interviewed individually via zoom and asked to share strategies that they incorporated in the classroom and school to make these connections. Middle school teachers shared strategies and practices that facilitated identity development in their students. Participants in this study appeared to encourage identity development by encouraging introspection and extrospection in their classrooms. They recognized the importance of establishing class routines promoting self-regulation and developing empathy for others. They also created opportunities for students to discuss and learn about local and global topics in class. Their responses are compared and contrasted with past scholarship highlighting the importance of identity development for young people.

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)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0240.009
Scholarly communication0.0090.005
Open science0.0020.016
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.078
GPT teacher head0.381
Teacher spread0.303 · 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 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

Citations2
Published2023
Admission routes2
Has abstractyes

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