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Record W2050073670 · doi:10.1080/14649360701712636

Family leisure, family photography and zoos: exploring the emotional geographies of families

2007· article· en· W2050073670 on OpenAlexaff
Bonnie C. Hallman, S. Mary P. Benbow

Bibliographic record

VenueSocial & Cultural Geography · 2007
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsContext (archaeology)Interpretation (philosophy)SociologyFamily lifePhotographyPsychologySocial psychologyVisual artsGender studiesHistoryArtComputer science

Abstract

fetched live from OpenAlex

In this paper we explore the significance of the zoo as a place for family leisure and the emotional work of sustaining a positive family life. Zoos are understood as culturally laden places, widely identified as locations for family-friendly leisure and as stages for practicing family and then capturing and memorializing this behavior in and through family photographs. Zoo family photos become souvenirs of quality family time, depicting the time and emotional investment made in the social relations captured in the images. We draw on an interdisciplinary mix of literatures and use this as context for the interpretation of a sample of family zoo photographs, illustrating our findings with examples drawn from public and personal sources. In so doing we seek to better understand the significance of family leisure environments, and specifically zoos, as places facilitating the emotional work of building and maintaining family connection and interaction.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.305
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations81
Published2007
Admission routes1
Has abstractyes

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