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Record W7025048444

Supporting the Development of Healthy Ethnic and Cultural Identities in Adolescents: Recommendations for Multicultural Counselling Practices

2022· other· en· W7025048444 on OpenAlexaboutno aff

Bibliographic record

VenueNational University System Repository (National University System) · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismEthnic groupIdentity (music)Cultural identityContext (archaeology)PopulationCultural diversityIdentity formation
DOInot available

Abstract

fetched live from OpenAlex

Adolescence is a stage in which awareness of being different significantly increases and an effort toward identity development begins. With recognition that adolescence is a difficult period of identity exploration, the focus of this inquiry was to gain a better understanding on how to support bi-cultural/ multicultural youth in developing a sense of self, which can include supporting them in their own exploration and formation of their different cultural identities. The workshop developed in chapter 3, proposed some recommendations that counsellors can adapt to individual client sessions, or try in a group setting, with the goal of supporting bi-cultural/multicultural teenagers in their own ethnic/cultural identity exploration and affirmation processes. Supporting the development of healthy cultural identities appears to be an important task, as being able to form strong positive cultural identities tends to be linked to positive psychological outcomes. As counsellors, when working with bi-cultural/multicultural client’s talking about race, ethnicity and culture is crucial. To avoid these topics is to ignore the context of someone’s life. It is important that counsellors feel comfortable supporting their teenage clients with different areas of identity exploration, and with the growth in a diverse population within Canadian society, pieces of identity exploration might well include formation of their cultural identities.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.784
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.318
Teacher spread0.263 · 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 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
Published2022
Admission routes1
Has abstractyes

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