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Record W4245847160 · doi:10.32920/ryerson.14662071

Desiring a balanced identity : a Heideggerian phenomenological inquiry into the pregnancy experiences of newcomer women to Canada living with HIV

2021· preprint· en· W4245847160 on OpenAlexaffabout
V. Logan Kennedy

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTheme (computing)Phenomenology (philosophy)Interpretative phenomenological analysisIdentity (music)Situational ethicsHuman immunodeficiency virus (HIV)Meaning (existential)Qualitative researchPregnancySociologyPsychologyGender studiesSocial psychologyMedicineEpistemologyPsychotherapistSocial scienceFamily medicineAesthetics

Abstract

fetched live from OpenAlex

The pregnancy experiences of newcomer women to Canada living with HIV is an important area within maternal health research which to date has been unstudied. Hence, the purpose of this study was to explore the meaning of pregnancy for newcomer women living with HIV. Heideggerian phenomenology was used as the methodology and guiding framework. Five women living in an urban setting in Ontario, Canada were interviewed. Through data analysis and using the four existentials of human existence Desiring a Balanced Identity emerged as the overarching theme of the pregnancy experiences of the five women. This overarching theme was intimately connected with the four essential themes which were uncovered during data analysis. These themes were The Situational Self, Living with the Good and the Bad, Support and Acceptance, and The Future Seems Brighter. Recommendations and implications for education, practice and organizational policy, and research are provided in light of the study findings.

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)0.008
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 score0.421
Threshold uncertainty score0.846

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0320.027
Scholarly communication0.0080.004
Open science0.0020.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.326
Teacher spread0.279 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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