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Abstract

Metaphor of modality in the Hallidayan linguistic framework is manifested through a transition from implicit modal expressions to explicit modal expressions, encompassing metaphor of modalization and metaphor of modulation. This article conducts a corpus-based investigation to examine the prevalence of metaphors of modalization in English academic writing. The study, which relies on data from the British National Corpus (BNC), reveals that modal expressions are more frequently used in less technical texts (i.e., in spoken texts rather than in written texts with regard to mode, in fiction texts rather than in academic texts with regard to genre, and in hard science texts rather than in soft science texts with regard to discipline). Furthermore, explicit subjective and explicit objective modal expressions exhibit opposite distribution patterns across modes, genres, and academic disciplines. Based on this general distribution pattern, this study then examines three distinct groups of PhD dissertations. It becomes evident that Chinese English as a Foreign Language (EFL) writers employ significantly fewer subjective projecting clauses compared to proficient native English writers in their academic writing. This difference arises from the rigorous training Chinese EFL learners receive, emphasizing the avoidance of authorial identity in academic writing. This study hereby concludes that while English academic writing may be becoming less formal, author involvement should not be encouraged in relatively more technical academic texts.

Plain language summary

The purpose of this study is to investigate the employment of modal expressions showing the author’s stance in English academic writing and to compare the types of modal expressions used by Chinese EFL academic writers and those by native English academic writers based on large-scale corpora. The findings are as follows: (1) modal expressions do not tend to occur in academic texts; (2) Of the two types of metaphorical expressions, explicit projecting clauses are more prevalent in the more technical texts and subjective projecting clauses are more prevalent in the less technical texts; (3) Chinese EFL writers use significantly smaller number of subjective projecting clauses than their native English counterparts in academic writing; (4) Author involvement is not a characteristic feature of academic texts even though academic writing is becoming less formal. This study is helpful for training Chinese EFL learners to write proficient academic texts.

Keywords

academic writing Chinese EFL writers corpus-based grammatical metaphor metaphor of modalization modal expressions

Introduction

Academic writing has traditionally been characterized by its non-interactivity, high lexical density, and impersonal tone, as noted by various scholars (e.g., Banks, 2008; Baratta, 2010; Biber, 2006; Hyland, 2006, 2009; Liardét, 2016; Schleppegrell, 2001). However, there is a growing assumption that academic writing is undergoing a shift toward reduced formality (Adel, 2008; Foster, 2005) and increased subjectivity (Hyland & Jiang, 2017). Some studies, such as those by Biber & Finegan (1989) and Hundt & Mair (1999), also suggest that academic writing is adopting a more spoken style (Praminatih et al., 2018). Furthermore, it is increasingly “considered to be a persuasive endeavor” (Hyland, 2011, p. 181), with writers employing reporting verbs (Thompson & Ye, 1991) to explicitly convey their opinions on propositions.

Reporting verbs play a crucial role in constructing a particular type of modal expression that creates interpersonal metaphor of modality in the Hallidayan sense (Halliday, 1985, 1994; Halliday & Matthiessen, 1999, 2004, 2014). As Liardét (2018, p. 66) suggests, “metaphors of modality are an important resource in the construction of academic texts.” If this holds true, we might anticipate a higher prevalence of explicit modal expressions in academic texts compared to other types of texts.

The primary aim of this study is to examine the distribution of modal expressions that convey an authorial stance in English across modes, genres, and academic disciplines. Additionally, we aim to compare the different modal expressions employed by Chinese English as a Foreign Language (EFL) academic writers and proficient native English academic writers. For these aims, we will conduct a corpus-based study of metaphor of modality in English academic writing. A brief overview of the metaphor of modality is provided in the following section, and the research methodology is outlined in Section “Methodoly.” Sections “Distributions of Modal Expressions in the BNC” and “Modal Expressions in the PhD Dissertations” present the findings regarding the distribution of modal expressions in the British National Corpus (BNC), Chinese EFL academic writing, and native English academic writing, respectively. The results will be discussed in Section 6.

Preliminaries of Metaphor of Modality

A fundamental function of language is to enact social processes (Halliday & Matthiessen, 1999) in the communication between the speaker and the hearer. The speaker adopts specific speech roles to establish their relationship with the hearer. Halliday (1985, 1994) recognized two fundamental speech roles: giving and demanding. The commodity that is given or demanded may be goods-&-services or information. These speech roles, in conjunction with the exchanged commodities, enact four fundamental speech functions: offer, command, statement, and question. See Table 1.

Table 1.

Basic Speech Functions (Halliday, 1994, p. 69).

	(a) Goods-&-services	(b) Information
(i) Giving	“Offer”	“Statement”
(i) Giving	Can I give you this teapot?	He gave her the teapot.
(ii) Demanding	“Command”	“Question”
(ii) Demanding	Give me that teapot!	What did he give her?

The variations in speech functions presented in Table 1 are contingent upon the choices available within the subject and finite elements (Yang, 2019). These two constituents, the subject and the finite, constitute the Mood of the clause. Typically, the finite element is realized as an auxiliary verb. When a modal verb functioning as the finite element serves to convey the speaker’s evaluation or assessment of the status of what is being said. The assessment is gradable in “construing the semantic space between the positive and negative poles” (Halliday & Matthiessen, 2014, p. 692). This type of gradation of evaluation or assessment is referred to as modality. For example, the modal verbs in (1) illustrate the degrees of modality:

(1) a. It must be the best of its kind. (BNC_miscellaneous) [high]

b. It should be substantially nutritious. (BNC_miscellaneous) [median]

c.It may be a case of reduced capacity. (BNC_academic) [low]

According to Halliday (1994), modality can be categorized into two main types: modalization and modulation. Modalization, the indicative type, involves conveying the degrees of probability and usuality, while modulation, the imperative type, pertains to expressing the degrees of obligation and inclination. Modalization is primarily concerned with the speaker’s opinion regarding the information given or demanded, whereas modulation pertains to the exchange of goods-&-services between the speaker and the hearer. Both types of modality can be construed along two orientations: they can be either subjective or objective, and they can be either implicit or explicit. Table 2, sourced from Halliday & Matthiessen (2014, p. 693), provides an overview of these distinctions.

Table 2.

Modality Type and Orientation Combined*

		Subjective		Objective
		Implicit	Explicit	Implicit	Explicit
Modalization	Probability	Mary’ll know	I think → Mary knows	Mary probably knows	It’s likely that Mary knows
Modalization	Usuality	Fred’ll sit quite quiet		Fred usually sits quite quiet	It’s usual for Fred to sit quite quiet
Modulation	Obligation	John should go	I want → John to go	John’s supposed to go	It’s expected that John goes
Modulation	Inclination	Jane’ll help		Jane’s keen to help

Note that we did not find projecting verbs that realize explicit subjective usuality or it is + adj. constructions that realize explicit objective inclination and that boldface means modality.

Implicit subjective modalities are realized as modal verbs, whereas implicit objective modalities are typically realized as modal adverbs. Explicit subjective modalities are typically realized as subjective projecting clauses, whereas explicit objective modalities are realized as objective projecting clauses. Both types of projecting clauses, whether subjective or objective, have the effect of diminishing “the validity while enhancing the negotiability and the arguability of instances” (Yang, 2019, p. 190). Consequently, these clauses are regarded as metaphorical expressions of modality, a perspective aligned with the insights of Halliday (1994), Taverniers (2003), and He (2021).

Metaphor of modality is a specific type of grammatical metaphor that arises from the reorganization of meaning at the lexicogrammatical stratum. Grammatical metaphor, initially proposed by Halliday (1984), encompasses two primary categories: ideational metaphor and interpersonal metaphor. As stated by Halliday & Matthiessen (1999, p. xi), “language evolved, in the human species, in two complementary functions: construing experience, and enacting social processes.” The reconstrual of experience creates ideational metaphor, while the reenactment of social processes creates interpersonal metaphor.

For example, the clause complex in (2a) construes a sequence at the semantic stratum. This sequence is realized as a single clause in (2b), where the two clauses are nominalized into two nominal groups, and the paratactic conjunction so is verbalized as resulted in. Therefore, (2a) is the congruent realization, while (2b) is considered as an incongruent or metaphorical realization.

(2) a. The driver drove the bus too rapidly down the hill, so the brakes failed.

b. The driver’s overrapid downhill driving of the bus resulted in brake failure.

Halliday (1998, p. 191)

The congruent realization is defined as “the typical ways of saying things” (Halliday, 1994, p. 343) or as the realization that “will be selected in the absence of any good reason for selecting another one” (Halliday, 1984, p. 14). In contrast, the metaphorical realization is recognized as a form of expression that is “not expressed through the most typical (and highly coded) form of representation” (Halliday, 1978, p. 180).

Interpersonal metafunction is realized through the systems of mood and modality, and therefore, interpersonal metaphor also encompasses metaphor of mood and metaphor of modality. According to Halliday (1985), for example, (3a) and (4a) represent the congruent realizations of mood and modality, respectively, and (3b) and (4b) represent the metaphorical realizations.

(3) a. Open your mouth, please, so that we can shove this in.

b. Kyle, can you open your mouth so we can shove this in?

(Taverniers, 2008, p. 84)

(4) a. Probably that pudding never will be cooked.

b. I don’t believe that pudding ever will be cooked.

(Halliday, 1994, p. 354)

Grammatical metaphor can be understood as the joining of semantic categories, as proposed by Halliday & Matthiessen (1999). In the example of (2b), both the two nominalizations the driver’s overrapid downhill driving of the bus and brake failure join figure with participant, and the verbalization result in joins relator with process. Therefore, ideational metaphor arises from the semogenic rank-shift from clause to group or from group to word (Halliday & Matthiessen, 1999).

Metaphor of modality arises from the semogenic transcategorization from the implicit domain to the explicit domain (He & Yang, 2014). In the case of (4b), for example, the implicit objective modal expression probably has transformed into the explicit objective modal expression I don’t believe, thus creating metaphor of modality. This is because explicit modal expressions are, strictly speaking, considered metaphor of modality (Halliday, 1994; Taverniers, 2003). According to Yang (2019), the transcategorization from the subjective domain to the objective domain also gives rise to metaphor of modality. Therefore, explicitation and objectification are the two orientations that lead to the creation of metaphor of modality (He, 2021).

Implicit subjective modal expressions represent the only congruent realization of modality, and explicit objective modal expressions do not directly stem from the transcategorization of implicit subjective modal expressions. Therefore, explicit objective modal expressions are considered second-order metaphor of modality. For example:

(5) a. He must be forty or more. (BNC_fiction) [implicit subjective]

b. The position is surely much simpler than this. (BNC_academic) [implicit objective]

c. I guess they transferred the call. (BNC_fiction) [explicit subjective]

d. It is possible that glasses will become a thing of the past. (BNC_newspaper) [explicit objective]

Given that metaphor of modality is considered an important resource in academic text construction (Liardét, 2018), one might expect all the three types of metaphorical modal expressions to be more prevalent in the academic texts than in the non-academic texts. However, it is important to note that subjective projecting clauses, while metaphorical, do not necessarily represent a defining feature of academic writing. Academic language is typically characterized by “objective evaluation that projects an authoritative stance to a non-interacting audience” (Liardét, 2018, p. 65). Similarly, modal adverbs are metaphorical but being implicit is not either a characteristic feature of academic writing, as metaphor of modality “allows personal stance or human reference to be explicit” (He, 2021, p. 52). In this context, it is the objective projecting clauses that stand out as a characteristic feature of academic writing. These clauses align with the objective and authoritative nature of academic discourse, where authors often project their arguments and findings in an objective and authoritative manner to engage with a non-interacting audience.

Academic writing provides a platform for individuals to demonstrate their advanced language skills, as observed by Adam and Artemieva (2002). It is also reasonably expected that individuals with higher language abilities would be more inclined to produce technical academic texts (He & Yang, 2018). In line with this reasoning, it is anticipated that native English academic writers would generate more technical academic texts than Chinese EFL academic writers. This expectation aligns with the notion that native speakers often have a deeper and more intuitive understanding of the language, which can lead to the production of more specialized and technical academic writing.

In the present research, our initial focus will be on examining the distribution patterns of different types of modal expressions in the BNC. Upon establishing a foundational distribution pattern based on the BNC, we will proceed to delve deeper into the utilization of modal expressions by Chinese EFL academic writers in comparison to native English academic writers. The hypotheses that underlie the research presented in this paper are as follows:

(1) Explicit objective modal expressions tend to occur in the more technical texts rather than in the relatively less technical texts.

(2) Chinese EFL academic writers are expected to use fewer metaphorical modal expressions in their academic writing compared to native English academic writers.

Methodology

Corpus

For the investigation into the use of metaphors of modalization in English, we will examine the distribution patterns of different types of modal expressions using the data from the BNC. Based on these distribution patterns, we will further analyze PhD dissertations authored by Chinese EFL academic writers and proficient native English academic writers. The BNC has been chosen as our primary data source due to its extensive size (comprising 100 million words) and its inclusion of both spoken and written texts, offering a range of modes. The written sub-corpus of the BNC encompasses various genres, including fiction, newspaper articles, magazines, academic writing, non-academic texts, and miscellaneous materials. Within the academic genre, there is further categorization by discipline, such as medicine, natural science, law & education, engineering, and humanities & arts. The academic section of the spoken sub-corpus is also organized by discipline, facilitating the examination of the distributions of modal expressions across modes, genres, and disciplines.

In line with Becher’s (1989) categorization, the disciplines of medicine, natural science, and engineering are classified as hard sciences, while law & education, social science, and humanities & arts are categorized as soft sciences. The BNC is available online (https://www.english-corpora.org.bnc), making it a convenient and valuable resource for retrieving relevant constructions related to various types of modal expressions.

For the exploration of modal expressions used by Chinese EFL academic writers, we compiled a balanced academic corpus. This corpus includes 100 PhD dissertations in linguistics authored by Chinese EFL academic writers, as well as 100 PhD dissertations in linguistics and 100 PhD dissertations in physics which represents a typical discipline in the hard sciences, authored by proficient native English writers. It is important to note that the Chinese EFL academic writers included in this study are considered advanced users of English as a foreign language. They have achieved the highest-level English language proficiency test certificate, which is a requirement for admission into a PhD program in linguistics. This selection criterion ensures that the Chinese EFL writers in the study possess a high level of English language proficiency.

These dissertations were randomly selected from online academic databases such as the CNKI Theses & Dissertations Database (https://oversea.cnki.net/kns?dbcode=CDMD) and ProQuest Dissertations & Theses (PQDT) Global (https://search.proquest.com/pqdtglobal). All these dissertations were published in English in recent years, specifically between 2017 and 2021.

The total size of this English-Chinese academic corpus amounts to 15,747,070 words. It is important to note that, to ensure data effectiveness, we manually excluded elements such as tables of contents, lists of tables and figures, formulas, references, appendices, acknowledgments, and other discipline-specific symbols. This exclusion leaves only the main bodies of text for analysis, as indicated in Table 3.

Table 3.

Sizes of the Two Corpora.

BNC			PhD dissertation
Sub-corpus		Size (words)	Sub-corpus	Size (words)
Spoken		9,963,663	Chinese EFL L.	6,779,854
Written	Fiction	15,909,312	Native English L.	5,172,509
	Magazine	7,261,990	Native English S.	3,794,707
	Non-academic	16,495,185
	Newspaper	10,466,422
	Academic	15,331,668
	Miscellaneous	20,835,159
Total		96,263,399	Total	15,747,070

Data Collection

In the present research, we will retrieve such typical modal expressions as modal verbs and modal adverbs construing implicit modalities, and modal projecting clauses construing explicit modalities. Modal verbs have the potential to realize both modalization and modulation, concepts that are closely related to the traditional notions of epistemic modality (related to knowledge and probability) and deontic modality (related to necessity and obligation) (Taverniers, 2008). It is observed that modal verbs followed by be or have, as shown in (6), mostly realize modalization; whereas modal verbs followed by a lexical verb, as shown in (7), mostly realize modulation, although there are exceptions. For example, may in (8) can also realize modulation. For data effectiveness, we will only retrieve modal verbs that are followed by be or have for modalization.

(6) a. He must be a fluent and persuasive speaker. (BNC_academic)

b. They must have done this for at least ten minutes. (BNC_academic)

(7) a. Party must do its duty. (BNC_newspaper)

b.You should try working on E6 at 3.00 am. (BNC_magazine)

(8) Sudden electrical death may occur early after blocking a coronary artery. (BNC_academic)

Our research will proceed by comparing the distributions of the four types of modal expressions related to modalization. It is worth noting that individuals often “have indefinitely many ways of expressing their opinions” (Halliday & Matthiessen, 2014, p. 689). To maintain focus and clarity, we will specifically select typical modal expressions as examples, following the proposals of Halliday & Matthiessen (2014), as outlined in Table 4. This approach will help us analyze and compare these selected modal expressions in a more structured and manageable manner.

Table 4.

Typical Modal Expressions of Modalization in English.

	Implicit		Explicit
	Subjective	Objective	Subjective	Objective
Probability	Modal verb [be, have]	Perhaps, certainly, hardly, probably, possibly, definitely, maybe, surely	I [think, know, guess, believe, suppose, consider, assume, doubt], I am [certain, sure, doubtful, confident]	It’s [likely, certain, possible, sure, probable]
Usuality	Modal verb [be, have]	Sometimes, rarely, never seldom, frequently, occasionally, commonly, often, always, usually		It’s [usual, common, rare, seldom, occasional]

Using these selected modal expressions, we retrieved a total of 828,291 concordance lines from the BNC and 83,596 concordance lines from the PhD dissertations, as indicated in Tables 5 and 6. These concordance lines will serve as the basis for our analysis and comparison of modal expressions in these two datasets.

Table 5.

Data Retrieved from the BNC.

		Implicit		Explicit		Total
		Subjective	Objective	Subjective	Objective	Total
Spoken		46,288	39,111	40,151	344	125,894
Written	Fiction	61,839	66,966	20,528	381	149,714
	Magazine	27,329	22,243	3,127	437	53,136
	Newspaper	45,014	20,089	3,666	500	69,269
	Non-academic	69,269	42,322	2,481	1,499	115,571
	Academic	84,961	47,154	1,616	2,589	136,320
	Misc	106,253	63,186	6,883	2,065	178,387
	Sub-total	394,665	261,960	38,301	7,471	702,397
Total		440,953	301,071	78,452	7,815	828,291

Table 6.

Data Retrieved from the PhD Dissertations.

	Implicit		Explicit		Total
	Subjective	Objective	Subjective	Objective	Total
Chinese L.	24,866	15,933	843	643	42,285
Western L.	18,102	9,563	1,501	633	29,799
Western S.	8,322	2,706	58	426	11,512
Total	51,290	28,202	2,402	1,702	83,596

Data Analysis

Since the sub-corpora differ in size, it is essential to normalize the collected data to frequencies per million words. This normalization will facilitate the comparison of distributions across modes, genres, and disciplines. To assess whether any differences in these distributions are statistically significant, we will employ the Pearson’s Chi-square test (Pearson, 1900). In this analysis, we will set the significance level at .01 for the critical value. The formulas for conducting the Pearson’s Chi-square test are as follows:

$χ^{2} = \sum \frac{{(Observe d_{ij} - Expecte d_{ij})}^{2}}{Expecte d_{ij}}$ (1)

$Expecte d_{ij} = \frac{row tota l_{i} \times column tota l_{j}}{n}$ (2)

in which i and j represent the rows and the columns, respectively, in the contingency table, and n is the total number of observations. The effect size can be measured with equation (3) if df = 1 or equation (4) if df > 1:

$Φ = \sqrt{\frac{χ^{2}}{n}}$ (3)

$Crame r^{'} s V = \sqrt{\frac{Φ^{2}}{\min (row tota l_{i} - 1, column tota l_{j} - 1)}}$ (4)

in which $Φ$ represents effect size and df is the abbreviation of degree of freedom. The specific equation used depends on the degrees of freedom in analysis. These equations help quantify the effect size and assess the practical significance of the observed differences in the contingency table.

In addition, we will also test whether the distributions of the four types of modal expressions are positively or negatively correlated in SPSS using the bivariate correlation test.

Distributions of Modal Expressions in the BNC

In this section, we will explore the distributions of the four types of modal expressions related to modalization across different modes, genres, and disciplines in the BNC. This analysis aims to provide insights into how these modal expressions are used within various contexts and fields of study.

Mode Distributions of Modal Expressions

As is shown in Table 5, we collected 125,894 instances of modal expressions from the spoken sub-corpus and 702,297 instances from the written sub-corpus. To facilitate comparison, we normalized the raw frequency of each type of modal expression to the frequency per million words. The total normalized frequency of the four types of modal expressions in the spoken sub-corpus (12,019) is higher than that in the written sub-corpus (7,908). Additionally, both implicit and explicit modal expressions are more frequent in the spoken sub-corpus (8,571 and 3,448 occurrences, respectively) compared to the written sub-corpus (7,443 and 465 occurrences, respectively).

This distribution trend suggests that modal expressions, as a whole, are more prevalent in the spoken sub-corpus compared to the written sub-corpus with regard to mode. Furthermore, there is a notable difference in the frequency of explicit modal expressions between the spoken and written sub-corpora, with explicit modal expressions being significantly more common in the spoken sub-corpus (χ² = 1,572.294, df = 1, p < .01). The correlation strength for this difference is modest (Φ = .281).

Subsequently, we converted the total normalized frequency for each of the four types of modal expressions to equal total frequencies. See Figure 1, where the frequencies are adjusted to achieve parity across the four modal expression types. This conversion allows for a balanced comparison of the different modal expression types within our analysis.

Figure 1.

Mode distributions of modal expressions in the BNC.

Figure 1 shows that the distributions of the four types of modal expressions exhibit significant differences between the spoken sub-corpus and the written sub-corpus (χ² = 6,927.388, df = 3, p < .01), with a moderate correlation strength (Φ = .436). Modal verbs display a similar distribution trend in both sub-corpora, while modal adverbs are more prevalent in the spoken sub-corpus compared to the written sub-corpus.

Furthermore, the distributions of the two types of implicit modal expressions are significantly different (χ² = 63.221, df = 1, p < .01), albeit with a weak correlation strength (Φ = .059). On the other hand, the two types of explicit modal expressions are distributed in opposite directions and significantly differ in the two sub-corpora (χ² = 6,872.465, df = 1, p < .01), showing a strong correlation strength (Φ = .614). Subjective projecting clauses are more prevalent in the spoken sub-corpus, while objective projecting clauses take priority in the written sub-corpus. The relatively higher frequency of explicit modal expressions in the spoken sub-corpus is primarily contributed by subjective projecting clauses.

The analysis reveals that modal expressions are indeed sensitive to mode, and the mode distribution of explicit objective modal expressions aligns with our initial hypothesis. However, the distributions of implicit objective modal expressions and explicit subjective modal expressions do not follow a similar pattern. While both types of modal expressions occur more frequently in the spoken sub-corpus compared to the written sub-corpus, there are notable differences. Specifically, in the spoken sub-corpus, modal adverbs make up 56.87% of all the modal adverbs in both sub-corpora, whereas subjective projecting clauses account for a substantial 89.90% of all such clauses. These disparities suggest that the mode sensitivity of different types of modal expressions can vary significantly.

It is important to note that the text types in the two sub-corpora may not be directly equivalent. For example, the spoken sub-corpus may include academic lectures, which can be more technically oriented than some fiction texts that may have a more oral-like quality. To ensure the effectiveness of the data, we selected the same sections, such as natural science, social science, law, and humanities, from both the spoken sub-corpus and the academic genre of the written sub-corpus. We then proceeded to compare the distributions of the four types of modal expressions within these shared sections in the two sub-corpora, as presented in Table 7. This approach allows us to make more accurate comparisons by focusing on similar text types and disciplines.

Table 7.

Modal Expressions in the Selected Four Disciplines of the Spoken and the Written Sub-Corpora of the BNC.

	Spoken				Written				Total
	Implicit		Explicit		Implicit		Explicit
	Subj.	Obj.	Subj.	Obj.	Subj.	Obj.	Subj.	Obj.
Natsci	93	72	14	0	6,210	3,774	17	250	10,430
Sosci	734	979	491	7	21,344	14,546	0	709	38,810
Law	245	141	154	5	30,704	11,473	346	547	43,615
Arts	220	261	68	1	14,824	12,591	511	668	29,144
Total	1,292	1,453	727	13	73,082	42,384	874	2,174	121,999

In the selected sections, we observe that the total normalized frequency in the spoken sub-corpus (44,369) remains higher than that in the written sub-corpus (36,015), mirroring the distribution pattern presented in Table 5.

To facilitate a fair comparison, we converted the total normalized frequency in the written sub-corpus (36,015) to match that of the spoken sub-corpus (44,369), resulting in an equal total normalized frequency. With this equalization, we can more accurately compare the mode distributions of the four types of modal expressions in the four selected sections, as demonstrated in Figure 2.

Figure 2.

Mode distributions of modal expressions in the selected sections of the BNC.

Figure 2 shows that the distributions of the four types of modal expressions exhibit significant differences in the four selected disciplines across the two sub-corpora (χ² = 49,987.631, df = 3, p < .01), with a strong correlation strength (Φ = .558). Modal verbs and modal adverbs are distributed in opposite directions, and this difference is significant in the two sub-corpora (χ² = 1,098.213, df = 1, p < .01), though with a modest correlation strength (Φ = .117). Notably, modal adverbs are more prevalent in the spoken sub-corpus, while modal verbs are more common in the written sub-corpus.

Additionally, the two types of explicit modal expressions also exhibit opposite distributions, with a much more significant difference compared to the implicit modal expressions (χ² = 49,005.045, df = 1, p < .01) and a strong correlation strength (Φ = .782). Explicit subjective modal expressions dominate in the spoken sub-corpus, whereas explicit objective modal expressions take priority in the written sub-corpus. These findings highlight the discipline-based distribution patterns of modal expressions within the two sub-corpora.

The findings from Figures 1 and 2 reveal similar distribution trends, indicating that modal expressions are sensitive to mode. Moreover, these two sets of data are significantly correlated at the .01 level (r = .988, p = .000), further confirming the mode sensitivity of modal expressions.

It is interesting to note that explicit modal expressions are a metaphorical representation of implicit modal expressions, yet the two types of metaphor exhibit opposite distributions across modes. Explicit objective modal expressions are more prevalent in the written texts, while explicit subjective modal expressions are predominantly found in the spoken texts.

Furthermore, although modal adverbs and subjective projecting clauses are both metaphors of modality, their distributions significantly differ in the two sub-corpora. Both types tend to occur more frequently in the spoken sub-corpus when compared to modal verbs, which are the only congruent realization of modality.

Genre Distributions of Modal Expressions

In this section, we will investigate how modal expressions are distributed within different written text genres. As shown in Table 4, we collected 702,397 occurrences of modal expressions from the written sub-corpus of the BNC. To provide a clearer understanding of the distribution patterns, we present the normalized frequencies of these modal expressions across the six written genres in Figure 3.

Figure 3.

Genre distributions of modal expressions in the BNC.

Figure 3 shows that the four types of modal expressions are genre-sensitive (χ² = 22,080.122, df = 15, p < .01), with a modest correlation strength (Crame’s V = .262). Here are some notable genre-specific observations. Generally, objective projecting clauses are most prevalent in the non-academic, academic, and miscellaneous genres, while being least common in the fiction, magazine, and newspaper genres. Subjective projecting clauses dominate over objective projecting clauses in the fiction, magazine, and newspaper genres but are less frequent in the non-academic, academic, and miscellaneous genres. These two types of explicit modal expressions, subjective and objective projecting clauses, are metaphors of modality. It can also be seen that the four types of modal expressions exhibit similar distributions in the non-academic, academic, and miscellaneous genres, but they are oppositely distributed in the fiction genre.

A bivariate correlation test demonstrates that the frequencies in the non-academic, academic, and miscellaneous genres are significantly negatively correlated with those in the fiction genre, as shown in Table 8.

Table 8.

Correlation Test of the Distributions of Modal Expressions in the Four Genres.

		Non-academic	Academic	Miscellaneous
Fiction	Pearson Correlation	–.993*	–.965*	–.997*
Fiction	Sig.	.007	.035	.003
Non-academic	Pearson Correlation		.949	.988**
Non-academic	Sig.		.051	.012
Academic	Pearson Correlation			.945
Academic	Sig.			.055

Correlation is significant at the .01 level (2-tailed).

Correlation is significant at the .05 level (2-tailed).

Table 8 provides valuable information regarding the correlations between different genres in terms of modal expression frequencies. Non-academic and miscellaneous genres exhibit a significant positive correlation at the .05 level. This suggests that these two genres share some commonalities in terms of modal expression usage. However, neither of the two genres, non-academic and miscellaneous, is significantly correlated with the academic genre. This is attributed to the notably high frequency of explicit objective modal expressions in the academic texts, which creates a distinct distribution pattern. In contrast, the frequency of explicit subjective modal expressions is significantly high in the fiction texts, leading to a unique distribution pattern in this genre.

Overall, the distribution patterns observed in the academic and miscellaneous genres align more closely with the mode distribution patterns shown in Figures 1 and 2, indicating that genre and mode can have a substantial impact on the usage of modal expressions.

The observation that fiction texts are the least technical while academic texts are the most technical aligns with prior research (e.g., Copeck et al., 1997). The higher level of technicality in the academic texts can be attributed to linguistic features such as nominalization and verbalization, which serve to simplify sentence structures and increase the technicality of text (Martin, 1993). It is important to note that technicality is “a graded rather than a binary quality” (Copeck et al., 1997, p. 393).

Based on the dominance of explicit objective modal expressions in the written texts and explicit subjective modal expressions in the spoken texts, it is reasonable to assume that written texts tend to be more technical than spoken texts. In other words, explicit subjective modal expressions and explicit objective modal expressions exhibit opposite distributions across modes and genres. The former is more likely to occur in less technical texts, while the latter predominates in more technical texts.

Discipline Distributions of Modal Expressions

In this section, we will provide with a detailed analysis of the usage of modal expressions in the context of different academic disciplines. In the academic sub-corpus of the BNC, which encompasses both hard science and soft science texts, we collected a total of 136,005 instances of modal expressions. This dataset is further divided into 27,370 instances in hard science texts and 108,635 instances in soft science texts, as shown in Table 9.

Table 9.

Modal Expressions Retrieved from the Academic Sub-Corpus of the BNC.

		Implicit		Explicit		Total
		Subjective	Objective	Subjective	Objective	Total
Hard Sci.	Engineering	5,697	1,646	5	185	7,533
	Medicine	6,182	3,124	50	230	9,586
	Natsci	6,210	3,774	17	250	10,251
	Sub-total	18,089	8,544	72	665	27,370
Soft Sci.	Socsci	21,344	14,546	372	709	36,971
	Humanities	14,824	12,591	346	546	28,307
	Law	30,704	11,473	511	669	43,357
	Sub-total	66,872	38,610	1,229	1,924	108,635
Total		84,961	47,154	1,301	2,589	136,005

In the analysis of modal expression usage within the academic sub-corpus of the BNC, we find that the normalized total frequency of the four types of modal expressions in the hard science texts (27,164) is slightly higher than that in the soft science texts (26,740). To facilitate a fair comparison, the data has been converted to equal total frequencies, and the resulting distribution of the four types of modal expressions in the two sub-corpora is depicted in Figure 4.

Figure 4.

Discipline distributions of modal expressions in the academic texts of the BNC.

Figure 4 provides insight into the discipline sensitivity of the four types of modal expressions within the academic sub-corpus, highlighting the differences between hard and soft science disciplines. Generally, the distributions of the four types of modal expressions differ significantly between hard and soft science texts (χ² = 15,536.827, df = 3, p < .01), with a moderate correlation strength (Φ = .335). Modal adverbs tend to be more frequent in the soft science texts, while modal verbs are more prevalent in the hard science texts. The distributions of the two types of implicit modal expressions also differ significantly between hard and soft science texts (χ² = 434.928, df = 1, p < .01), with a weak correlation strength (Φ = .079). Subjective projecting clauses dominate in the soft science texts, while objective projecting clauses are more common in the hard science texts (χ² = 13,587.405, df = 1, p < .01), with a moderate correlation strength (Φ = .443).

This distribution trend is similar to the mode and genre distributions because soft science texts are less technical than hard science texts (He & Yang, 2018). Modal expressions play a role in signaling the technicality of academic texts across different disciplines.

Modal Expressions in the PhD Dissertations

The BNC-based research shows that modal expressions are mode-, genre-, and discipline-sensitive. Of the two types of implicit modal expressions, modal verbs tend to predominate in the relatively more technical texts, whereas modal adverbs exhibit the opposite distribution trend. Of the two types of explicit modal expressions, subjective projecting clauses are more prevalent in the relatively less technical texts, whereas objective projecting clauses are oppositely distributed. Modal adverbs and subjective projecting clauses share similar distribution trends. In this section, the distributions of modal expressions in the three groups of PhD dissertations will be explored, shedding further light on modal expression usage in academic writing.

Modal Expressions in the Native English Linguistics and Physics PHD Dissertations

In the comparison of the distributions of modal expressions, the research focuses on native English PhD dissertations in the fields of linguistics and physics. The normalized total frequencies in the two sub-corpora are 5,761 and 3,034, respectively. To facilitate a fair comparison, the data has been adjusted to equal total frequencies. The resulting distributions of the four types of modal expressions in the two sub-corpora are depicted in Figure 5.

Figure 5.

Modal expressions in western linguistics and physics dissertations.

Figure 5 shows a similar distribution trend to that shown in Figure 4. The distributions of the two groups of data shown in the two figures are significantly correlated at the .01 level (r = .868, p = .005), highlighting that linguistics dissertations can be considered typical soft science texts and physics dissertations as typical hard science texts. This finding further confirms that soft science texts are generally less technical than hard science texts.

Comparatively, modal expressions in the hard science texts in the academic genre of the BNC account for 42.94% as shown in Figure 4 and 29.8% in the native English physics dissertations as shown in Figure 5. This suggests that although informal and speech-like English might be a trend for the development of academic writing (Alipour & Nooreddinmoosa, 2018), this does not necessarily imply a higher degree of author involvement in academic writing, particularly in hard science texts. Academic writing continues to maintain a degree of formality and objectivity, especially in hard science disciplines.

Modal Expressions in Chinese EFL and Western Linguistics PhD Dissertations

In this section, a comparison was made between the distributions of modal expressions in Chinese EFL PhD dissertations of linguistics and native English PhD dissertations of linguistics. The normalized total frequencies of modal expressions in Chinese EFL linguistics dissertations and native English linguistics dissertations are 6,237 and 5,761, respectively. This indicates that Chinese EFL users tend to write less technical academic texts than their native English counterparts.

However, when the data was adjusted to equal total frequencies for the four types of modal expressions, the normalized total frequency in the Chinese EFL linguistics dissertations (12,958) became lower than that in the native English linguistics dissertations (15,711). This difference arises from the lower frequency of subjective projecting clauses in the Chinese EFL linguistics dissertations. This observation is depicted in Figure 6 and indicates that Chinese EFL writers utilize fewer explicit modal expressions, particularly subjective projecting clauses, compared to their proficient native English counterparts in the PhD dissertations of linguistics.

Figure 6.

Modal expressions in Chinese EFL and western linguistics dissertations.

Figure 6 shows that the distribution of implicit modal expressions in Chinese EFL linguistics dissertations differs from that in the native English linguistics and physics dissertations as shown in Figure 5. The primary distinction is the lower proportion of explicit subjective modal expressions in the Chinese EFL linguistics dissertations, accounting for 29.62%. In contrast, Chinese EFL linguistics writers use more modal adverbs than modal verbs, while their native English counterparts use more modal verbs than modal adverbs. These two datasets exhibit a significant correlation at the .05 level (r = .960, p = .04).

Explicit modal expressions exhibit opposite distribution trends in Chinese EFL and native English linguistics dissertations, as shown in Figure 6, and in native English linguistics dissertations and physics dissertations, as shown in Figure 5. The distributions of these two datasets are significantly negatively correlated at the .05 level (r = −.967, p = .033). This indicates that Chinese EFL academic writers use relatively fewer explicit subjective modal expressions than expected, which aligns with our hypothesis that Chinese EFL academic writers use fewer metaphorical modal expressions compared to native English academic writers in academic writing.

However, it is too early to draw a conclusion that Chinese EFL academic writers can write more technical texts than their native English counterparts due to the lower frequency of subjective projecting clauses. This is because the frequency of objective projecting clauses is also obviously lower in the Chinese EFL linguistics dissertations than in the native English linguistics dissertations.

Discussion

It is found from the BNC-based research that modal expressions are mode-, genre-, and discipline-sensitive. Specifically, explicit objective modal expressions tend to occur in the more technical texts rather than in the relatively less technical texts. This is in agreement with our first hypothesis. However, explicit subjective modal expressions are oppositely distributed in the two types of texts. This is not in agreement with our first hypothesis. The BNC-based research also finds that implicit objective and explicit subjective modal expressions are similarly distributed, both accounting for a larger proportion in the less technical texts than in the more technical texts. Further investigation, conducted using three groups of PhD dissertations, shows that modal expressions follow similar distribution patterns in native English linguistics and physics dissertations as in the soft science and hard science texts of the academic sub-corpus of the BNC. However, there is a notable difference in the distribution of modal expressions in Chinese EFL and native English linguistics dissertations. Chinese EFL academic writers tend to use fewer explicit subjective modal expressions than anticipated. This is not in agreement with our second hypothesis. In the following section, we will delve into a discussion of these research findings.

Metaphor of modality arises from the unidirectional “transfer of the opinion of the speaker from the subjective category to the objective category and from the implicit category to the explicit category” (He & Yang, 2014, p. 352). See Figure 7 quoted from He (2021).

Figure 7.

Orientations of metaphorization of modality.

In the realm of implicit modal expressions, modal adverbs occur more than modal verbs in the relatively less technical texts. Conversely, within the realm of explicit modal expressions, objective projecting clauses tend to occur more than subjective projecting clauses in the relatively more technical texts. It can be seen that the explicitation of modality is not necessarily a characteristic feature of academic writing, as suggested by Liardét (2018). It is the two orientations, that is, explicitation and objectification together that truly defines the characteristic features of academic writing, as proposed by He (2021).

Modal verbs are recognized as “the only congruent realizations of modality” (He, 2021, p. 63). The relatively lower frequency of modal verbs in the relatively more technical texts might be attributed to their potential to realize both modalization and modulation. For example, in (9a), must is employed to realize modalization, while in (9b), must serves to realize modulation.

(9) a. I know this must be difficult for you. (BNC_fiction)

b. And you must be patient a little longer, my dear Adolph. (BNC_fiction)

Comparatively, it is expected that modalizations would be more abundant than modulations in the more technical texts. This anticipation stems from the fact that modalization serves to convey the author’s evaluation or judgment of a given fact, whereas modulation serves to convey the author’s manipulation of or participation in an act. Many of the modal verbs extracted from both the BNC and the PhD dissertations are indeed employed to realize modulation. For example:

(10) a. The Arts Council should be abolished, he wrote. (BNC_Fiction)

b. You can have a steak at home, I mean. (BNC_Spoken)

It is also true that there are many modal verbs that are used to realize modalization. For example:

(11) a. You should get the same answer if you did them both. (BNC_Spoken)

b. Such changes may receive support from cabinet ministers and senior civil servants. (BNC_Academic)

Modal adverbs, however, realize only modalization. Academic writers tend to use modal adverbs for modalization rather than relying on modal verbs, which can also serve for modulation. This is the reason why modal adverbs are more prevalent than modal verbs to realize modalization in relatively less technical texts.

The two types of explicit modal expressions are the metaphorical realizations of modality. However, the explicitation of implicit modal expressions is not, in itself, the defining characteristic of academic writing. This means that subjective projecting clauses are not necessarily more prevalent in the relatively more technical texts. In academic writing, for example, writers tend to employ objective projecting clauses to realize modality and to avoid author involvement. This also explains why the normalized frequency of subjective projecting clauses is notably high among the four types of modal expressions in the fiction sub-corpus. The other three types of modal expressions are not author involved. From this perspective, it is author involvement that is the characteristic feature of the relatively less technical texts.

We observed a consistent distribution pattern in the comparison between native English linguistics and physics dissertations. This suggests that linguistics can be considered a representative discipline within the soft sciences, while physics represents a typical discipline within the hard sciences. However, Chinese EFL linguistics dissertations deviate from this distribution pattern.

In the context of academic writing instruction in Chinese EFL settings, Chinese EFL learners are often encouraged to minimize author involvement, as the use of the first-person singular pronoun I is considered an informal feature of academic texts (Chang & Swales, 1999). However, scholars like Tang & John (1999) and Hyland (2001) argue that I can be used to construct authorial identities in academic writing. Chinese EFL learners tend to prefer the first-person pronoun we over I in their academic writing (Leedham & Fernandez-Parra, 2017). The avoidance of the first-person singular pronoun I encourages Chinese EFL writers to use fewer objective projecting clauses in their academic writing. This accounts for the relatively lower frequency of objective projecting clauses and the higher normalized frequency of implicit modal expressions in Chinese EFL linguistics dissertations compared to native English linguistics dissertations.

Language has undergone a process of simplification (Bhatia, 1983; Foster, 1968), and simplicity in structure is a defining characteristic of academic writing (Halliday, 2004). The explicitation of implicit modal expressions can introduce complexity into sentence structures, which runs counter to the principles of language simplification and the characteristic of simplicity of academic writing. This is also evidence that metaphor of modality arises from the transcategorization between speech functions, and it is not appropriate to resort to rank-shift which creates ideational metaphor to explain the creation of interpersonal metaphor (He & Yang, 2014).

According to He (2021, p. 68), “interpersonal metaphor is not created from the upward rank-shift from clause to clause complex or from group to clause.” Upward rank-shift is not possible (Halliday, 2002). The objectification of subjective modalities is “to avoid a direct conflict between the communicators” (He & Yang, 2014).

In academic writing, writers “tend to perform their wishes, attitudes and judgments in an objective way, and to hide their subjective determinations in their objective expressions” (He & Yang, 2014, p. 357). As elucidated by He (2021, p. 68), “the departure from the explicit subjective orientation results in the shift of modal responsibility embodied in subjecthood from the speaker or writer to somebody or something else.” In this context, objectivity emerges as a genuine hallmark of academic writing.

Conclusion

This study delved into the distribution patterns of modal expressions across various types of texts. The research conducted using the BNC dataset found that metaphorization encompasses two primary orientations: explicitation and objectification. However, neither of these orientations, in isolation, can be unequivocally designated as the defining characteristic of academic writing. Instead, it is the convergence of explicitation and objectification that demonstrates sensitivity to mode, genre, and discipline. Consequently, this study concludes that author involvement stands out as a distinctive characteristic of relatively less technical texts.

Based on this distribution pattern, we proceeded to investigate how modal expressions are distributed in the academic writing of Chinese EFL users. It became evident that the distribution pattern of modal expressions in native English linguistics and physics dissertations closely mirrors that in the soft science and hard science texts of the BNC. However, in Chinese EFL linguistics and native English linguistics dissertations, the distribution of the four types of modal expressions deviates from this regularity.

The distributions of implicit modal expressions in the two groups of linguistics dissertations are similar to those in the soft science and hard science texts. However, explicit modal expressions exhibit an opposite distribution trend. It is worth noting that explicit modal expressions are the metaphor of modality of implicit modal expressions, but this type of metaphorization arises from the explicitation of implicit modalities within the semantic domains. This is a process of unidirectional transcategorization rather than a process of rank-shift that creates ideational metaphor, as explained in previous research (He & Yang, 2014). This phenomenon can also be attributed to the objectification of subjective modalities.

The implications of this study are two-fold. First, it is not necessarily the case that metaphors of modality are an important resource for constructing academic texts as suggested by Liardét (2018). Instead, it underscores that it is primarily the explicit objective modal expressions that play a crucial role in academic writing. Second, the findings suggest that Chinese EFL academic writers should exercise caution when using modal adverbs in an attempt to achieve objectivity. They should bear in mind that their proficiency in academic writing is not solely reflected in their English language skills but also in their ability to write academically.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research,authorship,and/or publication of this article: This research is supported by China National Social Science Fund (21BYY043).

ORCID iD

Qingshun He

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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