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Record W7155755877

The Experience of Students Achieving High School Success While Attending a Vancouver Alternate Secondary School

2022· dissertation· en· W7155755877 on OpenAlexaboutno aff
Douglas Louis Matear

Bibliographic record

VenueKU ScholarWorks (The University of Kansas) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsFlexibility (engineering)PersonalizationFocus groupMental healthFocus (optics)
DOInot available

Abstract

fetched live from OpenAlex

AbstractThis study investigated the experiences of students who attended a Vancouver Alternate Secondary School (VASS) program and achieved a regular high school diploma, which is known as a Dogwood Diploma, in the province of British Columbia, Canada. Through interpretive and semi-structured interviews, the recent graduates shared their experiences and how they achieved graduation. The research study looks at their experiences from an asset-based framework instead of focusing on their individual deficits.The research revealed the structures and qualities of the VASS programs that supported the participants. The 11 participants mentioned the flexibility of instruction in the VASS programs, the smaller sites and smaller classes, the personalization of instruction, the healthy relationships established with the VASS staff, the staff’s persistence in reaching out to connect with them, and the participants’ ability to focus on their future endeavours. The participants saw these VASS programs as a viable option for students entering high school.The participants mentioned the importance of belonging and connecting with both the VASS staff and students. Even when they were unable to attend school due to complex reasons such as mental health concerns, the staff still reached out to check in with them and encouraged them to return. These participants see their time at VASS as instrumental in helping them graduate.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.014
GPT teacher head0.302
Teacher spread0.288 · 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.

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
Published2022
Admission routes1
Has abstractyes

Explore more

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