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Record W3214979712 · doi:10.32920/ryerson.14668341.v1

The "good" mother: experiences of Canadian adolescent mothers living in rural communities

2021· preprint· en· W3214979712 on OpenAlexaffabout
Karen Campbell

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsNarrativePsychologyConstruct (python library)Developmental psychologyCoping (psychology)Rural areaExperiential learningSocial psychologyClinical psychologyMedicinePedagogy

Abstract

fetched live from OpenAlex

Adolescent mothers and their children are at risk for suboptimal health outcomes making adolescent motherhood a public health concern. However, the experiences of rural-living adolescent mothers are not well understood. Using Lieblich, Tuval-Mahiach, and Zilber's (1998) narrative methodology approach, the experiential accounts of three rural-living adolescent mothers was explored. Reflecting Goffman's (1959) presentation of self, the findings of this study revealed how adolescent mothers attempted to construct and present their notion of being a good mother, while coping with complicating rural factors. The need to present as a good mother, the lack of anonymity associated with rural living, and geographical barriers had particular implications for the way in which adolescent mothers access and use professional and personal supports. Maintaining relationships with the infants' fathers, even when that relationship exhibited unhealthy characteristics, was important for study participants. Implications for practice, education, and recommendations for future research are discussed.

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)0.001
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 score0.189
Threshold uncertainty score0.380

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.003
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.064
GPT teacher head0.367
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

Citations0
Published2021
Admission routes2
Has abstractyes

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