MétaCan
Menu
Back to cohort
Record W37945059 · doi:10.1891/rtnp-2022-0152

Joan Wallach Scott, ed. Women's Studies on the Edge

2009· article· en· W37945059 on OpenAlexaffvenue
Elizabeth Groeneveld

Bibliographic record

VenueThirdspace · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Medicine
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEnhanced Data Rates for GSM EvolutionPsychoanalysisGerontologyPsychologySociologyArt historyArtMedicineComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

<b>Background and Purpose:</b> The purpose of this qualitative study was to evaluate experiences of the COVID-19 pandemic on freshman and sophomore residential nursing students in relation to personal development. Findings are examined through the lens of Chickering's seven vectors of psychosocial development to better understand the implications of nursing students' challenges during COVID-19. <b>Methods:</b> A convenience sample of residential nursing students completed surveys eliciting narrative descriptions of the consequences of the COVID-19 pandemic on their lives while in college. <b>Results:</b> Five main themes were identified as personal consequences of the pandemic: loss of connection with peers and instructors, loss of focus, loss of motivation, physical isolation, and emotional isolation. Findings were discussed through the lens of Chickering's seven vectors of psychosocial development to better understand the implications of students' COVID experiences. <b>Implications for Practice:</b> The results of the study suggest that students may have experienced obstacles from the effects of COVID-19, which may affect their psychosocial and identity development. An understanding of the personal consequences of COVID-19 on residential nursing students may assist faculty and administrators as they develop opportunities for social interactions that serve as a foundation for psychosocial development.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score1.000

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 studies0.0010.001
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 head0.052
GPT teacher head0.275
Teacher spread0.223 · 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 designNot applicable
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

Citations1
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueThirdspaceSame topicHistory of Science and MedicineFrench-language works237,207