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Record W7132873604

Success Stories in Urban Science Education

2025· dissertation· W7132873604 on OpenAlexaffabout
Kristina Ann Salciccioli

Bibliographic record

VenueTSpace · 2025
Typedissertation
Language
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsScientific literacyScience educationInterpretation (philosophy)Qualitative researchSocial science educationWork (physics)Science, technology, society and environment educationScience communicationNature of Science
DOInot available

Abstract

fetched live from OpenAlex

This qualitative phenomenological study gives voice to the stories of in-risk high school students who successfully negotiated a path to university science programs. In-depth, semi-structured interviews were completed with 17 students from one urban Canadian secondary school. This work explored the following research questions: 1. (a) Why did these in-risk high school students choose science pathways in postsecondary education? (b) What are their lived experiences and what challenges did they face? 2. What did these students identify as enabling factors that supported their interest in pursuing science? Theories related to science identity, self-efficacy, expectancy value, ethic of care, and scientific literacy informed the analyses and interpretation of my findings in deductive and inductive ways. This work revealed that many participants had an interest in science from an early age, and a scientific way of viewing their world. For some, science was viewed as a “refuge” from their lives, a way out of poverty, a subject, and a process that reflected their personal sensibilities and a way to contribute to society. Participants’ understandings of science were nuanced. Traditional views of science as stable and predictable emerged, along with more contemporary understandings of science as a means to foster change, agency, and hope. Participants identified factors that supported their choices to pursue science careers, including: the importance of teachers (as role models and counter-stereotypes); access to rich high school experiences including exceptional pedagogies, access to enrichment programs, and extra-curricular experiences in science; the importance of a caring school environment; and having a network of support from teachers, family, peers, communities, and local programs. This study deliberately moved away from deficit models to frame the participants’ pathways to postsecondary science programs; instead, it focused on the voices of these students to reveal their inspirational stories of resilience, their dedication to their studies, and their success in pursuing a science career.

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)0.011
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 score0.043
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0280.022
Scholarly communication0.0120.005
Open science0.0030.014
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.053
GPT teacher head0.503
Teacher spread0.450 · 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
Published2025
Admission routes2
Has abstractyes

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