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Learning and Identity: Life, Work and Citizenship

2012· book-chapter· en· W2491072601 on OpenAlexfundaboutno aff
Adrienne S. Chan, Barbara Merrill

Bibliographic record

VenueAdvances in gender research · 2012
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsnot available
FundersUniversity of the Fraser Valley
KeywordsCitizenshipPedagogyIdeologyIdentity (music)NarrativeReflexivityCohortPsychologyGender studiesSociologySocial sciencePolitical scienceMedicine

Abstract

fetched live from OpenAlex

Purpose – This chapter highlights two studies, one in Canada and one in the United Kingdom. The Canadian study focused on the examination of student experiences with respect to specific ‘difficult’ content in the classroom. The purpose of the study was to identify ways that were effective and engaging for students to learn. The UK study examined issues of access, retention and drop-out of non-traditional students in higher education. The study examined the learning experiences of women who returned to learning after being out of the education system for some time.Methodology – The Canadian study used surveys and interviews. Participants were recruited on the basis of their enrolment in specific classes. The UK study used interview samples drawn from student data in three universities. In each university, a cohort was followed and interviewed three times while in another cohort students were interviewed in their first year of study and different cohort in their final year of study.Approach – Both studies use a feminist, narrative approach that relies on reflexive engagement in the research process.Findings and implications – The studies highlight that the classroom is a place where dialogue and engagement occur; where the identities of the participants and their learning are in a dynamic process; and where the learners challenge attitudes and ideologies such as capitalism and forms of marginalisation. The studies revealed that learning has a social value and entreats women to reconsider their lives, work and citizenship.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.771
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.131
GPT teacher head0.455
Teacher spread0.323 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2012
Admission routes2
Has abstractyes

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