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Record W3158002756 · doi:10.82308/41249

Looking at high school dropout problems from students' perspectives : finding a solution

2003· article· en· W3158002756 on OpenAlexaboutno aff
Joan M. Gordon

Bibliographic record

VenueeScholarship@McGill (McGill) · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsDropout (neural networks)Mathematics educationPsychologyPedagogyComputer science

Abstract

fetched live from OpenAlex

Should we be concerned about the more than 30 percent national dropout rate? Can anything be done to intervene successfully? Many students who drop out of school have the intellectual ability to complete college (Howard and Anderson, 1978). If this is so, then our educational institutions are failing them and doing them a tremendous disservice (Committee of Canadian Council for Exceptional Children, 1992). This research investigates the high school dropout phenomenon in Quebec through the "eyes" of potential dropouts. The project examines the high school dropout phenomenon from the perspective of students who are at risk of leaving school prematurely. The objectives of the research are to investigate how potential high school dropouts perceive success, and to find out what program reforms these students believe are necessary to keep them in school. In the data analysis the students' schooling experiences are critically examined, and factors such as students' perception of public high schools, social affairs schools, teachers and their view of success are considered. These considerations are made within the conceptual framework of a variety of sociological theories in education. Social Affairs schools are special schools reserved for youths who are wards of the court, and those who are in the care of Youth Protection because they cannot live at home. This study provides richly descriptive narrative accounts of the students' experiences, thoughts and feelings. The study gives voice to high school students who are at risk of dropping out, and of their views of what their needs are to be successful in school. Data collected from this study can be used to develop suitable programs for students. The study concludes by signaling a call to parents, teachers, governments, policy-makers, and caregivers to listen to children and to involve them in matters that are important to them---such as their views of how they can achieve school success.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.031
GPT teacher head0.312
Teacher spread0.282 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations2
Published2003
Admission routes1
Has abstractyes

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