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Record W36034720 · doi:10.1016/j.paid.2022.111869

Assessing the quality of the requirements process

2011· dissertation· en· W36034720 on OpenAlexfundaboutno aff
M.P. Jochemsen

Bibliographic record

VenuePersonality and Individual Differences · 2011
Typedissertation
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaFonds pour la Formation de Chercheurs et l'Aide à la Recherche
KeywordsBrainstormingChecklistProcess (computing)Quality (philosophy)Waterfall modelComputer scienceProcess managementSet (abstract data type)Management scienceEngineering managementEngineeringSoftwareArtificial intelligence

Abstract

fetched live from OpenAlex

Self-determination theory proposes that intrinsic aspirations protect against negative mental health outcomes by satisfying people's basic psychological needs of autonomy, relatedness, and competence. The present study investigated this relationship using two four-wave prospective longitudinal studies which followed undergraduate students across the Canadian academic calendar (September to May). The first was conducted across 2018-19 and the second across 2019-20. By comparing these two samples, we examined whether baseline levels of intrinsic aspirations moderated the impact of the COVID-19 pandemic on the development of depressive symptoms. Three main findings emerged, the first being that students reported higher levels of depressive symptoms in Spring 2020 than in Spring 2019. Second, students with more intrinsic aspirations in the pre-pandemic sample (2018-19) experienced fewer depressive symptoms from December to May while students with more intrinsic aspirations in the pandemic sample (2019-20) experienced more depressive symptoms during this period. Lastly, the latter relationship was mediated by need frustration, whereby students with higher levels of intrinsic aspirations experienced greater need frustration during the pandemic year. Together, these findings suggest that although intrinsic aspirations typically protect against negative psychological outcomes, the unique need frustrating context of the pandemic made them a risk factor for depression.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.477
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.188
GPT teacher head0.398
Teacher spread0.211 · 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.

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
Published2011
Admission routes2
Has abstractyes

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