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Record W4231308423 · doi:10.24124/2014/bpgub1009

Goals and hope in adolescent at-risk high school students.

2014· dissertation· en· W4231308423 on OpenAlexfundno aff
Patience S. Cox

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsnot available
FundersUniversity of Northern British Columbia
KeywordsSession (web analytics)Set (abstract data type)Scale (ratio)PsychologyGoal settingMedical educationMathematics educationPedagogySocial psychologyMedicineGeographyComputer science

Abstract

fetched live from OpenAlex

This study utilizes Snyder et al.'s (1991) hope theory as a tool in cooperation with Feldman, Rand, Kahle-Wrobleski (2009) goal-specific hope scale to look at how hope theory, as defined by Snyder, can play a role in improving and supporting students to achieve their goals. Twenty-two students in a senior Alternative Education program in northern British Columbia participated in the study from September 2012 to January 2013. Students participated in a three month study where they completed Snyder's Adult Hope Scale (AHS) and Feldman's Goal Specific Hope Scale (GSHS), which required them to set a specific academic goal at the beginning of the process. They participate in five structured goal and motivation individual sessions during the study. They were monitored and completed the AHS after each session. At the end of the study, each student also returned to the GSHS and measured their level of hope specific to the goal they had set at the beginning of the study. Although there were no statistically significant changes in individuals' overall hope scale, there were significant changes in hope as it related to the specific goal students had set for themselves.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.317
Teacher spread0.308 · 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 designObservational
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
Published2014
Admission routes1
Has abstractyes

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