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Journeying through Resilience and Transition: Exploring Substance Abuse, Mental Health, and Well-being in Maria Campbell’s Halfbreed

2024· article· en· W4404339421 on OpenAlexaboutno aff
C. Sindhu, N. Priya

Bibliographic record

VenueInternational Research Journal of Multidisciplinary Scope · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsnot available
FundersVIT University
KeywordsMental healthResilience (materials science)Substance abusePsychologyTransition (genetics)Well-beingSubstance usePsychological resiliencePsychiatryPsychotherapistMaterials scienceChemistry

Abstract

fetched live from OpenAlex

This research paper intensely analyses Maria’s challenges as depicted in Maria Campbell’s autobiographical Novel Halfbreed. It examines her metamorphosis from childhood to adulthood and the self-empowerment that resulted from her hardships. The article also looks at how Indigenous women have historically been marginalized and highlights Campbell’s story as an example of a young Native woman’s tenacity in Metis society. It also investigates the historical marginalization of Indigenous women and emphasizes Campbell’s narrative as a testament to the resilience of a young Native woman within the Metis community. It centers on Maria Campbell’s masterful portrayal of her journey from vulnerability to empowerment in Halfbreed. It provides insights into Campbell’s obstacles in life and how resilience enables her to respond to them with fortitude and flexibility. It discusses how mental health influences one’s thoughts, emotions, and capacity to cope with stress, highlighting its significance in fostering resilience and maintaining a sense of purpose and self-worth. The article delves into the societal implications of mental health struggles, particularly examining issues such as Xenophobia and sexism and their impact on interpersonal relationships. The article connects the protagonist’s narrative with larger societal concerns, revealing the complex relationship between mental health and systemic obstacles. It also emphasizes Campbell’s mission to highlight these issues and the need for societal transformation. It also provides valuable insights into the complex nature of mental well-being and its significant impact on both individuals and communities.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score0.501

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 studies0.0000.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.354
Teacher spread0.309 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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