Construct · 4 fields · 4 citations

Where does concentration collide?

One name. Different field. Different construct. One map.

● jingle · one word, four constructs Nearest construct by meaningattention-based viewcompare the meanings
How to read this

Every construct on the map is compared with every other by the meaning of its definitions, and the closest one is surfaced here. The nearest construct to concentration is attention-based view.

Hold this as a prompt, not a verdict. Two constructs sitting close in meaning is a reason to read them side by side and decide for yourself whether they are one idea under two names. It is not proof that they are. Compare the meanings in the Collider.

concentration4 CONSTRUCTSConcentrationIUPAC · AMOUNT PER VOLUMEMarket concentrationBAIN · MARKET STRUCTUREFocused attentionJAMES · FOCUSED ATTENTIONConcentration boundsBOUCHERON · TAIL BOUNDS

Spokes are fields; dashed arcs are shared lineage. Tap a field for its definition, unit, and measures.

2026

Drag to watch the word get claimed. Each field appears at the publication date of the earliest source cited for it. Tap a year to see which.

Chemistry

Amount of a substance per unit volume

In chemistry, concentration is the amount of a dissolved substance present in a given amount of solution, most often expressed as amount concentration or molarity, the moles of solute per litre of solution. It is an intensive quantity: it does not depend on how much of the mixture you have, and it governs how fast reactions run and where chemical equilibria settle. The IUPAC Compendium of Chemical Terminology (the Gold Book), compiled by McNaught and Wilkinson in 1997, gives the standard definitions of concentration and its related quantities. The referent is a physical ratio of matter to volume in a beaker, not a market dominated by a few firms, a mind fixed on a task, or a random variable clustering near its average.[1]

Unit
One instance is a solute amount divided by solution volume, e.g. moles per litre
Recovery means
Not applicable
Measured by
Determined by titration, spectrophotometry, or other assays calibrated against known standards

Industrial economics

How far a few firms dominate a market

In industrial economics, concentration measures how far a small number of firms account for most of the activity in a market, captured by tools such as the concentration ratio, the combined share of the largest few firms, or the Herfindahl-Hirschman index, the sum of squared market shares. Bain's 1951 study Relation of Profit Rate to Industry Concentration linked how concentrated an industry was to how profitable its firms were, helping found the structure, conduct, and performance tradition. Here concentration is a property of a whole industry, read from the distribution of sales across competitors, and it has nothing to do with molarity in a flask, focused attention in a person, or the spread of a random quantity.[2]

Unit
One instance is an index over an industry's firm shares, e.g. a concentration ratio or HHI
Recovery means
Not applicable
Measured by
Computed from firms' market shares in sales, output, or assets within a defined market

Psychology

Sustained focused attention on a task

In psychology, concentration is holding attention steadily on one task or stream of information while resisting distraction. William James, in his 1890 The Principles of Psychology, described attention as the mind taking possession of one object out of several, its focalization and concentration of consciousness, and treated that narrowing as the core of an effortful mental state. The referent is a person's directed and sustained focus, felt, reportable, and measured by performance, not a ratio of matter in a solution, the grip of a few firms on a market, or the clustering of a random variable.[3]

Unit
One instance is a person's sustained focus on a single task over a stretch of time
Recovery means
Attention lapses and returns, and focus is restored by rest, motivation, or re-engaging the task
Measured by
Indexed by performance on sustained-attention and vigilance tasks, error and reaction-time lapses, and self-report

Probability and statistics

How tightly a random variable clusters near its mean

In probability and statistics, concentration describes how tightly a random variable stays near its expected value, so that large departures from the average become very unlikely. Concentration inequalities, such as Chebyshev's and Chernoff's bounds, put explicit limits on the probability of straying far from the mean, and the broader concentration of measure phenomenon says that a well-behaved function of many independent variables is almost constant. Boucheron, Lugosi, and Massart's 2013 book Concentration Inequalities gathers this theory into a single account. The referent is a mathematical statement about the spread of a random quantity, not a chemical ratio, a market's structure, or a person's focus.[4]

Unit
One instance is a bound on the probability that a random variable deviates from its mean
Recovery means
Not applicable
Measured by
Established by proof, using moment, variance, or exponential-moment arguments to bound tail probabilities

Next

Run it through the Collider, or take the citations with you.

See how concentration sits against neighbouring constructs in the Collider, or export every reference on this page in one click.

Open in ColliderExport BibTeXReport this collision

Nearby collisions

attention5 fields · 10 citationsjingle · one name, five constructsaffinity3 fields · 4 citationsjingle · one word, three constructsarousal3 fields · 4 citationsjingle · one word, three constructs

References

  1. McNaught, A. D., & Wilkinson, A. (1997). IUPAC Compendium of Chemical Terminology (the "Gold Book"). Blackwell Scientific Publications. https://doi.org/10.1351/goldbook
  2. Bain, J. S. (1951). Relation of profit rate to industry concentration: American manufacturing, 1936-1940. The Quarterly Journal of Economics, 65(3), 293-324. https://doi.org/10.2307/1882217
  3. James, W. (1890). The Principles of Psychology (Vol. 1). Henry Holt and Company.
  4. Boucheron, S., Lugosi, G., & Massart, P. (2013). Concentration Inequalities: A Nonasymptotic Theory of Independence. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199535255.001.0001

Cited on this page?

Confirm your construct, or correct us.

If your work is cited behind one of these entries, you know better than we do whether we captured the meaning right. Confirm it, suggest an edit, or dispute it, and your name goes on the entry as an author who has checked it, linked to your ORCID.

Claim your construct