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Record W4401769584 · doi:10.1080/13642537.2024.2384852

Wished I’d been there: Reflections on the special issue’s articles as refracted through my appreciations for qualitative researchers’ innovativeness

2024· article· en· W4401769584 on OpenAlexaff
Tom Strong

Bibliographic record

VenueEuropean Journal of Psychotherapy & Counselling · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologySociologyQualitative researchEpistemologyAestheticsSocial scienceArtPhilosophy

Abstract

fetched live from OpenAlex

Since the early 1990s, the innovativeness and critical responsiveness of qualitative researchers in studying psychotherapy and mental health has been astonishing to witness. A social constructionist or postmodern (e.g. with narrative, solution-focused, and collaborative approaches) therapist who went on to conduct, teach, and supervise qualitative research, I bring an appreciative view of this recent history to comment on the articles of this Special Issue. This history shows qualitative researchers developing and refining their methods to pose new questions and ways of answering them in line with therapist curiosities about meaning making. Qualitative research also became a tool for surfacing social justice concerns, or for answering or addressing questions in novel contexts. The innovativeness of qualitative researchers often derives from how new ideas, concerns, and sense-making practices are honed by methodical rigors that extend beyond the one-off understandings or hunches therapists develop through working with clients. Though use of any method has limitations on what can be claimed from its use, what matters most is that good qualitative research offers useful understandings. From this appreciation of qualitative research’s recent history and its potential usefulness to therapists and mental health workers, I selectively comment on the following articles.

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)0.030
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.839
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0300.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.727
GPT teacher head0.668
Teacher spread0.059 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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