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Record W2200225589

An examination of self-identified reasons for student departure at a small liberal education institution in Canada

2009· dissertation· en· W2200225589 on OpenAlexaboutno aff
Sonia Richards

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2009
Typedissertation
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionLiberal arts educationNonprobability samplingVariety (cybernetics)Persistence (discontinuity)Medical educationPsychologyData collectionEducational institutionHigher educationPedagogyPopulationSociologyPolitical scienceMedicineSocial scienceLawDemographyEngineering
DOInot available

Abstract

fetched live from OpenAlex

This study explored the self-reported reasons why students, who were registered as first year students at a small, primarily undergraduate liberal arts institution, left after only one year of study. Data collection involved a mixed methods approach and the results were analyzed using a phenomenological approach, examining variables; social and academic integration, residential living, family commitments and finances. This study's findings confirmed there are a variety of reasons that students leave an institution after one year of study. The major findings revealed the reasons that the students self-reported for leaving were the inability to meet new friends, lack of career planning, unavailable program options and the cost to attend the institution. Because purposive sampling was used in the study, results cannot be generalized to the wider population but are consistent with the literature on student persistence. Based on the findings, the study did identify several recommendations that would be helpful in assisting with an institution's student persistence plans.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science 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 score0.252
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0010.001
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 head0.024
GPT teacher head0.328
Teacher spread0.304 · 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
Published2009
Admission routes1
Has abstractyes

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