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Record W3136408332 · doi:10.58809/kpis6387

Thematic Analysis of Social Issues in Ten Young Adult Novels

2019· article· en· W3136408332 on OpenAlexaboutno aff
Brittany Sale

Bibliographic record

VenueJournal of Applied and Educational Research · 2019
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
Fundersnot available
KeywordsFriendshipThematic analysisThematic mapPsychologyContent analysisHistorySociologyLiteratureQualitative researchSocial psychologySocial scienceArtCartographyGeography

Abstract

fetched live from OpenAlex

The purpose of this study was to complete a thematic analysis on ten randomly selected young adult novels published in the year 2018. Novels were selected based on the criteria of (1) being published in the year 2018, (2) age-appropriate for middle and high school students, (3) written in English and (4) not being a part of a series. The novels were published in the United States or Canada. The thematic analysis was conducted to determine recurring social issues presented in the novels that are affecting young adults. The novels examined in this study are: What If It’s Us, Swing, Unclaimed Baggage, When Elephants Fly, Meet the Sky, The Chaos of Now, A Very Large Expanse of Sea, Broken Things, Words We Don’t Say, and Sadie. This study suggested how to integrate the novels in a middle or high school setting and whether the novels could be used in a lesson or should be housed in a school library. Each novel was read, analyzed for themes, and categorized to determine main themes of the text. Every novel dealt with a different social issue including: addiction, death, loss, friendship, and school.

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)0.020
metaresearch head score (Gemma)0.041
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 score0.020
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.041
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.007
Science and technology studies0.0060.005
Scholarly communication0.0050.003
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.179
GPT teacher head0.556
Teacher spread0.377 · 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
Published2019
Admission routes1
Has abstractyes

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