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Record W3047397508 · doi:10.82396/cjcd.v16i1.3108

The Gap Year Dilemma: When a Purposeful Gap Year is the Answer to Career Unpreparedness

2021· article· en· W3047397508 on OpenAlexaffabout
April Dyrda, Laura Hambley, Kerry B. Bernes, Mike Huston

Bibliographic record

VenueThe Journal of Macrodynamic Analysis (Memorial University of Newfoundland) · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsMount Royal UniversityUniversity of LethbridgeUniversity of Calgary
Fundersnot available
KeywordsDilemmaCLARITYPopularityPsychologyPopulationHigher educationGender gapMedical educationPedagogyMathematics educationSocial psychologySociologyPolitical scienceDemographic economicsDemographyMedicine

Abstract

fetched live from OpenAlex

Students entering post-secondary are shown to be increasingly underprepared for the educational and career related demands associated with higher education. Quickly becoming a global trend and an attractive alternative to entering post-secondary directly from high school, a purposeful gap year increases student academic motivation and performance. Despite gaining popularity, there is limited research exploring the implications of the gap year among a North American population. The present study sought to examine how university students come to make career choices and the implications that a gap year has for this process. Two hundred first year undergraduate students studying at a large university in Western Canada completed a survey about their career plans. An analysis of the results comparing gap year and non-gap year students using a non-parametric ANOVA revealed that while students who had taken a gap year benefited from enhanced personal experiences and indicated that taking this time out of school was a positive experience, they continued to lack confidence and clarity regarding their career plans. These and other findings are discussed and serve to enhance an understanding of the potential benefits and implications of a purposeful gap year

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.249
Teacher spread0.230 · 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 designQualitative
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
Published2021
Admission routes2
Has abstractyes

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Same venueThe Journal of Macrodynamic Analysis (Memorial University of Newfoundland)Same topicTourism, Volunteerism, and DevelopmentFrench-language works237,207