The Geometry of Culture: Analyzing the Meanings of Class through Word Embeddings

Austin C. Kozlowski, Matt Taddy, James A. Evans · American Sociological Review / arXiv · 2019 · digital-humanities · 10.1177/0003122419877135 · record kozlowski2019-geometry-culture
tag layer · index · concepts · authors · עברית
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How to read this page. The article itself is not reproduced here — this paper is not cleared for redistribution, so what follows is the tag layer alone. The evidence sentences are withheld with the article. The table at the foot lists every tag the record carries; each row names the facet it belongs to, and the whose words column says whether the tag records the paper's own wording or the tagger's sentence about the paper. Every tag links to each other paper in the corpus carrying it. The machine-readable edition of the same thing is the TEI file beside this one, where the tags live in standOff, and the article is at its publisher via the link below. When we have changed our mind. Some entries in the table begin with a word in capitals and the reason for it. EVIDENCE CORRECTED — the finding still stands, but we had quoted the wrong sentence from the paper, and the quotation has been replaced with the right one. RETRACTED — the entry itself was wrong; it stays on the page, marked, with the reason, rather than being deleted. WITHDRAWN AND REPLACED — the entry was wrong, and a corrected version of it appears in the entries below. Each mark carries its own reason, in brackets, because the reasons differ from one entry to the next. An entry we have WITHDRAWN is removed from this page and kept in the record, with its reason. A line reading Audit and a date is a later re-reading of the entry against its whole sentence: DOUBTFUL means it was kept, and the reason says what is loose about it. Quotation marks inside the tagger's sentence. Where a tag is the tagger's own sentence, a phrase in quotation marks inside it is borrowed from the paper — the tagger's wording around it is not. The paper's own sentence is the evidence quote for that row; on this page it is withheld with the article, and the article is at its publisher. Nothing inside quotation marks anywhere on this page is ours: if it is quoted, it is the paper's. Whose words a concept carries. A concept entry records a term the paper itself uses, so the term, the sense given for it, and its evidence are the paper's own words, quoted where the paper fixes them. This is the opposite of a sense entry in the tag table, which is the tagger's sentence about how the paper uses a term. Where a concept entry could not be grounded in the paper's words, the entry says so on its own row.
Other fields define these differently the same word, defined another way in another discipline
meaning 4 fields · class 3 fields · standard-deviation 3 fields · gender 2 fields · bootstrap 2 fields · confidence-interval 2 fields · and 3 more →

Tags on this paper

Every tag the record carries, each linking to every other paper in the corpus that carries it. A tag appears here whether or not its words occur in the article — the spans below are only the ones a sentence in this paper licenses. Of the 8 concept tags on this paper, 3 are grounded in a quoted sentence.
word embedding semantic space cultural dimension cosine similarity distributional semantics word embeddings semantic relations cultural categories building cultural dimensions as averaged vector-differences between antonym word pairs, then projecting words onto them vector space cultural dimensions class gender meaning corpus high-dimensional cultural associations neural-network Latent Semantic Analysis (LSA) relational model of meaning Bayesian bootstrap confidence-interval confidence intervals correlation Pearson mean mean of p-value standard-deviation standard deviation statistical-significance statistical significance variance system-or-tool-building

Legend

relation to other workclaim_relationshow this paper stands to another: agrees, contradicts, extends, qualifies
claim typeclaim_typethe shape of the claim: existence, mechanism, method, critique, prediction, null
concept edgeconcept_edgesan asserted relation between two concepts, with the sentence asserting it
conceptconceptsan idea the paper works with, quoted where the paper uses it
content tagcontent_tagsa finding, definition, quantity, statistic or variable named in the paper
controlcontrolsan experiment run to eliminate a rival explanation
limitationlimitationswhat the paper says its evidence cannot support
mechanismmechanismshow the reported effect is said to come about
methodmethodhow the paper produced its evidence
phenomenonphenomenonthe effect or regularity under study
sensesensesa distinct use of a term, quoted where the paper fixes it

The paper

The full text is not reproduced here. This article is not cleared for redistribution, so the page carries the tag layer only. Its evidence sentences are withheld; the grounding status remains with each tag, and the article itself is at https://doi.org/10.1177/0003122419877135. The reading view exists for the papers whose licence permits it.

Every tag on this page

claim_relations 6 · claim_type 1 · concept_edges 1 · concepts 3 · content_tags 18 · controls 1 · limitations 6 · mechanisms 1 · method 1 · phenomenon 1 · senses 3

Relations on this page carry a quotation for the claim. Where a relation was separately evidenced — and so tested against the vocabulary for its type — the row says so; none of 1 relation here carry that mark. The rest are the tagger’s reading of the sentence quoted beside them.

facettagfieldconf.whose words
claim_typemethod
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claim_typethe paper's words
phenomenoncultural dimensions in word-embedding spaces
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phenomenonthe paper's words
methodsystem-or-tool-building
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methodthe paper's words
mechanismsmechanisms
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mechanisms[0]the tagger's words
limitationsThe method needs a large corpus; subtle and complex cultural associations cannot be recovered from small bodies of text.
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what this limits: any application to a small corpus: WORD EMBEDDINGS ... REQUIRE A RELATIVELY LARGE BODY OF TEXT IF THE OUTPUT VECTOR SPACE IS TO CAPTURE SUBTLE AND COMPLEX ASSOCIATIONS
limitations[0]the tagger's words
limitationsRace could not be traced historically because the terminology shifted across the century, so the historical analysis was restricted to gender and class.
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what this limits: the absence of race from the historical analysis: UNDERTAKING THIS TASK EFFECTIVELY WOULD REQUIRE A DEEPER ENGAGEMENT WITH LINGUISTIC SHIFTS IN RACIAL TERMINOLOGY THAN IS FEASIBLE WITHIN THE SPACE CONSTRAINTS - the dimension is omitted for a vocabulary reason
limitations[1]the tagger's words
limitationsThe validating survey used a Mechanical Turk sample that is not representative of the US population.
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what this limits: the survey validation specifically: OUR SAMPLE CANNOT BE SAID TO BE REPRESENTATIVE OF THE GENERAL POPULATION OF THE UNITED STATES
limitations[2]the tagger's words
limitationsEmbedding projections capture semantic association in text, not material or on-the-ground social realities.
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what this limits: every substantive claim about culture: WORD EMBEDDINGS MODELS, BY DISTILLING INFORMATION FROM LOCAL WORD CO-OCCURRENCES, DO NOT PROVIDE DIRECT INFORMATION ABOUT MATERIAL, ON-THE-GROUND REALITIES
limitations[3]the tagger's words
limitationsThe confidence intervals depend on treating books and newspapers as independent draws from a population of cultural observations, which is stated as a condition rather than shown.
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about this quote: THE QUOTE IS AN ASSUMPTION, NOT A FINDING - the sentence opens 'If we assume that the texts' before it, and a page number ('29') sits between that opening and the quote. · what this limits: the confidence or credible intervals reported for distances and projections here: they follow from assuming the underlying texts are i.i.d. observations drawn from a population of cultural observations
limitations[4]1.0the tagger's words
limitationsThe method the paper displaces is criticised on reproducibility, which is the ground on which the new one is offered.
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what this limits: the comparison between close reading and embedding-based analysis: close reading is credited with advancing the field and criticised for clear limitations in reproducibility
limitations[5]1.0the tagger's words
controlsthe interpretation space sampled SYSTEMATICALLY - 1,775 antonym pairs taken from WordNet - rather than by selecting salient dimensions, with the reported dimensions restricted to those at the smallest angle to the focal ones
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eliminates: CHERRY-PICKING BY THE ANALYST. The paper names the charge it is answering: that researchers 'conveniently cherry-pick explanations to confirm…'. An unsupervised model yields far more readable structure than any paper reports, so the choice of what to report is where the freedom lives · outcome (stated by the tagger, no quotation): held
controls[0]0.95the tagger's words
conceptsword embeddings
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concepts[5]the paper's words
conceptssemantic relations
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concepts[6]the paper's words
conceptscultural categories
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concepts[7]the paper's words
sensesmeaning - OPERATIONALISED AS GEOMETRY: semantic relations between words represented as geometric relationships between vectors, which the paper calls a relational model of meaning
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senses[0]1.0the tagger's words
sensessemantic change - measured as CHANGE IN POSITION: a word's rate of semantic change taken to be the change in its overall position in the vector space
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senses[1]1.0the tagger's words
sensescultural categories - held by the intersectionality literature to be inseparable: their meaning changes as they overlap, so they cannot be isolated and understood independently
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senses[2]1.0the tagger's words
claim_relationsbuilds-on → word2vec (CBOW/skip-gram) and GloVe (from NLP)
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claim_relations[0]the tagger's words
claim_relationsextends → interpretive text analysis of culture (adding reproducibility)
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claim_relations[1]the tagger's words
claim_relationsextends → Bolukbasi et al. (2016) and Caliskan et al. (2017) on bias in word embeddings
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claim_relations[2]the tagger's words
claim_relationscontradicts → Bolukbasi et al. (2016) proposal to de-bias word embeddings
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claim_relations[3]the tagger's words
claim_relationsextends → Pierre Bourdieu's relational field theory / correspondence analysis
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claim_relations[4]the tagger's words
claim_relationsextends → Osgood's semantic differential method
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claim_relations[5]the tagger's words
concept_edgessemantic relations —operationalised-as→ word embeddings
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strength of the relation: 1
concept_edges[0]the tagger's words
content_tags20th — span of the gender/class coevolution analysis
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content_tags.quantities[0]the tagger's words
content_tags1970s — when LSA-type methods first appeared
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content_tags.quantities[1]the tagger's words
content_tags20,000 — example vocabulary size reduced by embeddings
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content_tags.quantities[2]the tagger's words
content_tagsprojecting words onto these dimensions recovers widely shared cultural connotations
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content_tags.findings[1]the tagger's words
content_tagsfeminine and masculine occupations sit at opposite poles of a gender dimension
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content_tags.findings[2]the tagger's words
content_tagsword embeddings capture more complex semantic relations than prior text methods
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about this quote: A PAGE NUMBER SITS INSIDE THIS QUOTE: the '2' between 'past modes of' and 'computational text analysis' is the page's number, not part of the sentence; read the quote with it deleted.
content_tags.findings[3]the tagger's words
content_tagsword embeddings
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content_tags.definitions[0]the tagger's words
content_tagsLatent Semantic Analysis (LSA)
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content_tags.definitions[1]the tagger's words
content_tagsrelational model of meaning
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content_tags.definitions[2]the tagger's words
content_tagsBayesian
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about this quote: QUOTE RECOVERED FROM THE PAPER'S OWN CHARACTERS. The recorded quote was LETTERS-ONLY IDENTICAL to this stretch of the staged text but not an exact substring of it - spaces, hyphens, ligature glyphs or mathematical operators differed, so it could never anchor. This is the file's own text between the same two letters: not produced by a rule about the damage, copied out of the file. Round-trip checked (the recovered span is letters-only equal to the original) and length-checked. The text as originally recorded is kept in evidence as extracted.
also in: Bayesian
content_tags.statistics[0]the tagger's words
content_tagsbootstrap
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also in: bootstrap
content_tags.statistics[1]the tagger's words
content_tagsconfidence-interval
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content_tags.statistics[2]the tagger's words
content_tagscorrelation
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also in: correlation
content_tags.statistics[3]the tagger's words
content_tagsmean
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also in: mean
content_tags.statistics[4]the tagger's words
content_tagsp-value
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about this quote: QUOTE RECOVERED FROM THE PAPER'S OWN CHARACTERS. The recorded quote was LETTERS-ONLY IDENTICAL to this stretch of the staged text but not an exact substring of it - spaces, hyphens, ligature glyphs or mathematical operators differed, so it could never anchor. This is the file's own text between the same two letters: not produced by a rule about the damage, copied out of the file. Round-trip checked (the recovered span is letters-only equal to the original) and length-checked. The text as originally recorded is kept in evidence as extracted.
also in: p-value
content_tags.statistics[5]the tagger's words
content_tagsstandard-deviation
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about this quote: QUOTE RECOVERED FROM THE PAPER'S OWN CHARACTERS. The recorded quote was LETTERS-ONLY IDENTICAL to this stretch of the staged text but not an exact substring of it - spaces, hyphens, ligature glyphs or mathematical operators differed, so it could never anchor. This is the file's own text between the same two letters: not produced by a rule about the damage, copied out of the file. Round-trip checked (the recovered span is letters-only equal to the original) and length-checked. The text as originally recorded is kept in evidence as extracted.
content_tags.statistics[6]the tagger's words
content_tagsstatistical-significance
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about this quote: QUOTE RECOVERED FROM THE PAPER'S OWN CHARACTERS. The recorded quote was LETTERS-ONLY IDENTICAL to this stretch of the staged text but not an exact substring of it - spaces, hyphens, ligature glyphs or mathematical operators differed, so it could never anchor. This is the file's own text between the same two letters: not produced by a rule about the damage, copied out of the file. Round-trip checked (the recovered span is letters-only equal to the original) and length-checked. The text as originally recorded is kept in evidence as extracted.
content_tags.statistics[7]the tagger's words
content_tagsvariance
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also in: variance
content_tags.statistics[8]the tagger's words

Interpretive choices

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