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Record W6928793170 · doi:10.3886/e154861

Differentiating Teachers’ Social Goals: Data and Analysis Files

2021· dataset· en· W6928793170 on OpenAlexaffabout

Bibliographic record

VenueICPSR Data Holdings · 2021
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsMcGill University
Fundersnot available
KeywordsPerspective (graphical)Relation (database)Social relationshipSocial relationSocial changeSocial competence

Abstract

fetched live from OpenAlex

These files contain the anonymized data used to create the tables and figures found in "Differentiating Teachers’ Social Goals: Implications for Teacher-Student Relationships and Perceived Classroom Engagement". <br><br>Please refer to the abstract for the paper below: <br><br>Whereas developing meaningful connections with students has long been documented as critical for promoting classroom engagement, teachers’ differing motives for building relationships with students remain underexplored. This study examined teachers’ social achievement goals from a multidimensional perspective in relation to teachers’ self-efficacy, teacher-student relationships, and perceived classroom engagement. Results from practicing K-12 teachers (N = 154) from across Canada showed three distinct goal orientations including social mastery-approach, social mastery-avoidance, and social ability goals (combining social ability-approach and social ability-avoidance goals). Teachers who aimed to develop better social skills with students (social mastery-approach goals) reported higher self-efficacy, better relationships with students, and greater classroom engagement. In contrast, social goal orientations focused on not losing connections with students (social mastery-avoidance goals) or being well-liked (social ability goals) did not correspond with self-efficacy or classroom outcomes. Implications concerning integrative pedagogies and growth mindsets pertaining to relationship building were discussed.<br>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.005
Research integrity0.0010.000
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 head0.038
GPT teacher head0.312
Teacher spread0.274 · 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
GenreDataset

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
Published2021
Admission routes2
Has abstractyes

Explore more

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