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Record W4405408825 · doi:10.18357/otessac.2024.4.1.378

Survivors of Complex Trauma as Adult Online Learners

2024· article· en· W4405408825 on OpenAlexafffundvenue
Hilary Schmidt

Bibliographic record

VenueThe Open/Technology in Education Society and Scholarship Association Conference · 2024
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsThompson Rivers University
FundersAthabasca University
KeywordsPsychology

Abstract

fetched live from OpenAlex

Complex trauma is both a product and a source of significant multidimensional inequality, including profound disruption to survivors’ educational trajectories. Nonetheless, educational researchers have not previously engaged with adult survivors who study online, contradicting the key principle of collaboration within a trauma-informed approach. This qualitative instrumental collective case study explored how adults with a history of complex trauma experience postsecondary open/online learning. Findings included participants’ struggles with executive functioning, challenges regulating emotion and dealing with a heightened perception of threat, re-experiencing trauma, negative beliefs about the self, and difficulties navigating relationships. These trauma impacts affected not only participants’ learning and course experience, but also their experience of applying, registering, and accessing financial aid. Nonetheless, participants are demonstrably skilled in managing the impacts of their trauma and are driven to learn, placing the highest intrinsic value on education. Top priorities for the implementation of trauma-informed educational practices identified by participants included establishing safety; trust and transparency; and empowerment, voice, and choice. Implications include enhancing equity and inclusion for survivors of complex trauma through the implementation of trauma-informed educational practices in open/online postsecondary contexts.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.060
GPT teacher head0.397
Teacher spread0.337 · 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
Published2024
Admission routes3
Has abstractyes

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