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Record W6984835856

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2024· other· pl· W6984835856 on OpenAlexaboutno aff

Bibliographic record

VenueDirectory of Open access Books (OAPEN Foundation) · 2024
Typeother
Languagepl
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsSnowball samplingTourismQuarter (Canadian coin)AccommodationSocial distancePandemicThematic analysis
DOInot available

Abstract

fetched live from OpenAlex

The aim of the study is to present the tourist plans of the inhabitants of Polish cities during the COVID-19 pandemic. A survey technique was used in the research with a questionnaire being disseminated for Facebook´s tourist thematic groups. Those recruited provided their friends with a link to the questionnaire via social media. Thus a snowball method was used and 402 respondents were obtained. Less than a quarter declared they did not want to go on a tourist trip in 2020 and the main reason was the prevailing pandemic and fear of coronavirus infection. However, the vast majority of respondents planned at least one tourist trip but a significant part abandoned any intention of travelling abroad for a holiday. The respondents mainly declared their willingness to stay in hotels and holiday resorts but assessed these facilities as the least safe in terms of epidemiology. The prevailing pandemic has been a source of much concern but the respondents were also worried about increased prices. Accommodation facilities were expected to undergo some form of disinfection along with the need to comply with social distancing restrictions and the wearing of masks.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.455
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0040.002
Science and technology studies0.0010.002
Scholarly communication0.0160.007
Open science0.0210.009
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.2820.114

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 head0.176
GPT teacher head0.528
Teacher spread0.351 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Explore more

Same venueDirectory of Open access Books (OAPEN Foundation)Same topicLGBTQ Health, Identity, and PolicyFrench-language works237,207