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Record W2017292918 · doi:10.1080/00220671.2012.753857

Analyzing the Discourse of Dropouts and Resilient Students

2013· article· en· W2017292918 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Journal of Educational Research · 2013
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversité du Québec à MontréalMcGill UniversityUniversité de Sherbrooke
FundersUniversité de SherbrookeMcGill University
KeywordsOutreachPsychologySet (abstract data type)Mathematics educationPedagogyMedical educationMedicineComputer science

Abstract

fetched live from OpenAlex

ABSTRACT The authors focused on high school students who were at risk of dropping out and examined why some of these students persevered and graduated while others ended up dropping out of school. Sixty resilient students and 80 dropouts participated in the study. Our results indicate that although learning difficulties were shared by participants, 4 types of abilities set the resilient students apart from dropouts: (a) inreach (using their own resources); (b) outreach (asking for help when needed); (c) establishing and maintaining positive relationships with teachers and friends while setting limits when necessary; and (d) planning, making choices and following through on decisions. It was also found that resilient students could count on lifelines, people they knew they could always rely on when they had difficulties.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.107
GPT teacher head0.577
Teacher spread0.470 · 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