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Record W2129820781 · doi:10.1080/10720537.2013.843479

Between Subject and Object: Using the Grammar of Verbs to Enhance the Therapeutic Construction of Personal Agency

2014· article· en· W2129820781 on OpenAlexaff
Nick Todd

Bibliographic record

VenueJournal of Constructivist Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSubject (documents)Object (grammar)FeelingAgency (philosophy)GrammarAction (physics)VerbPsychologySense of agencyLinguisticsPosition (finance)Social psychologyComputer scienceEpistemologyPhilosophyWorld Wide Web

Abstract

fetched live from OpenAlex

AbstractThe basic English language structure of subject-verb-object divides experience into positions that are socially as well as linguistically meaningful. Clients often seek counseling as a result of feeling acted upon (i.e., being in an object position with respect to the difficulties they are facing), and our work as therapists often entails assisting them to regain a subject position in which they can experience an increased sense of themselves as competent social agents. As the fulcrum between the object and the subject, verbs play a key role in effecting the transition from object to subject positions, and more generally in mediating linguistic constructions of personal agency. This article reviews ways in which we can use the grammar of verbs more deliberately to help clients shift from the object position of feeling acted upon to the subject position of taking effective action with respect to their difficulties. ACKNOWLEDGEMENTSI would like to thank Lyndsey Hampton, Yvon LaCour, Tara Perry, Rob Van Dyke, Allan Wade, and Mike Yudcovitch for helpful feedback on earlier drafts of this article. Thanks also to Eleanor Verbicky-Todd for her support in developing these ideas.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.812
Threshold uncertainty score0.402

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.345
Teacher spread0.321 · 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

Citations11
Published2014
Admission routes1
Has abstractyes

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