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Record W2115282919 · doi:10.1371/journal.pone.0135477

When Aspirations Exceed Expectations: Quixotic Hope Increases Depression among Students

2015· article· en· W2115282919 on OpenAlexaff
Katharine H. Greenaway, Margaret Frye, Tegan Cruwys

Bibliographic record

VenuePLoS ONE · 2015
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsCanadian Institute for Advanced Research
Fundersnot available
KeywordsDepression (economics)PsychologyHigher educationSocial psychologyClinical psychologyEconomics

Abstract

fetched live from OpenAlex

A paradox exists in modern schooling: students are simultaneously more positive about the future and more depressed than ever. We suggest that these two phenomena may be linked. Two studies demonstrated that students are more likely to be depressed when educational aspirations exceed expectations. In Study 1 (N = 85) aspiring to a thesis grade higher than one expected predicted greater depression at the beginning and end of the academic year. In Study 2 (N = 2820) aspiring to a level of education (e.g., attending college) higher than one expected to achieve predicted greater depression cross-sectionally and five years later. In both cases the negative effects of aspiring high while expecting low persisted even after controlling for whether or not students achieved their educational aspirations. These findings highlight the danger of teaching students to aspire higher without also investing time and money to ensure that students can reasonably expect to achieve their educational goals.

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)0.000
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 score0.033
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.095
GPT teacher head0.314
Teacher spread0.219 · 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 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

Citations30
Published2015
Admission routes1
Has abstractyes

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