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Record W1562670619

Other-Wise: The Case for Understanding Other Cultures in a Unipolar World.

2000· article· en· W1562670619 on OpenAlexaboutno aff
Leon E. Clark

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicJewish Identity and Society
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)WonderPopulationRest (music)Political sciencePsychologySociologySocial psychologyMedicineDemography
DOInot available

Abstract

fetched live from OpenAlex

TWENTY-FIVE YEARS AGO, hit upon an exercise have used around the world ever since, but mostly with high school and college students in the United States. have come to call this exercise Forced Migration Game, and this is how it works. Imagine that your government has decided that a certain percentage of your nation's population will have to move to another country permanently. (You might wonder why a government would want to do this. We don't have time to go into all the reasons right now, but take it from me, your government is a benevolent government, and it would not ask to leave if it weren't absolutely necessary.) Now, since your government is benevolent, it would like to make this forced migration as painless as possible, so it has distributed a form asking you to list the three countries where you would MOST like to live. Do that now. And remember, you will live in one of these countries for the rest of your life. Do you have your top three choices? Good. Now your government wants to make sure you've selected these countries for valid reasons, so it has asked you to write, next to each of your three choices, a word or two explaining why you have chosen these countries. Please do that now. The first half of the written exercise, focusing on positive choices, is now completed. (See an example of the form used with the exercise on p. 450.) The second half of the exercise runs as follows: Your forms have been sent to your government's Out-Migration Center and, much to everyone's surprise, there is a problem. It seems this process is much more complicated than anyone expected and it will not be possible to send everyone to his or her country of choice. But your government, being benevolent, certainly does not want to send you to a country you would not like to live in, so it has asked you to list the three countries where you would LEAST like to live for the rest of your life. Do that now, and next to each choice give two or three reasons for making the choice. At this point, ask students to volunteer their responses. Any country that gets a minimum of five to eight votes, depending on the size of the group, gets listed on the board with its vote total. The recorded lists, positive and negative, along with the major reasons for the choices, serve as an overview of the group's responses and the basis for discussion. Countries Most Like Their Own As might be expected, American students most often choose Western industrialized nations for their positive choices--countries most like their own. Over the years, the consistently most popular choices have been Britain and Australia, followed closely by Canada, Switzerland, Italy, and Sweden. One might expect to be the runaway first choice of American students, given its similarity and proximity to the United States, but American students often say they think of more as an extension of the U. S. than as a foreign country. The late Canadian writer Robertson Davies made a similar point when he said, Canada is the attic of North America. The most common reasons students give for their positive choices relate to culture, economics, and geography: lifestyle, strong economy (Australia); English, (Britain); people are culturally similar to me, good economy, beautiful landscape (Switzerland); language, climate, beaches (Australia); I identify with the culture, the values, and have family and friends there and speak the language (Denmark); familiar culture, proximity to family and friends in the U.S. (Canada); studied there and feel comfortable with the (Spain); I have friends there and know the language (Germany); It's beautiful, love Renaissance art, speak some Italian, the Alps (Italy); friendly people, cool summers, open-minded society, English spoken everywhere (Sweden); quiet, peaceful country, high standard of living, similar culture and language (New Zealand). …

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.879
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.072
GPT teacher head0.349
Teacher spread0.277 · 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 designTheoretical or conceptual
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

Citations2
Published2000
Admission routes1
Has abstractyes

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